WO2025091206A1

WO2025091206A1 - Configuration of entropy coding for channel state feedback

Info

Publication number: WO2025091206A1
Application number: PCT/CN2023/128238
Authority: WO
Inventors: Abdelrahman Mohamed Ahmed Mohamed IBRAHIM; Jay Kumar Sundararajan; Taesang Yoo; Chenxi HAO
Original assignee: Qualcomm Inc
Current assignee: Qualcomm Inc
Priority date: 2023-10-31
Filing date: 2023-10-31
Publication date: 2025-05-08
Anticipated expiration: 2026-04-30

Abstract

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF. The UE may transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. Numerous other aspects are described.

Description

CONFIGURATION OF ENTROPY CODING FOR CHANNEL STATE FEEDBACK

INTRODUCTION

Aspects of the present disclosure generally relate to wireless communication and specifically relate to techniques, apparatuses, and methods for conveying configuration information relating to the channel feedback.

Wireless communication systems are widely deployed to provide various services that may include carrying voice, text, messaging, video, data, and/or other traffic. The services may include unicast, multicast, and/or broadcast services, among other examples. Typical wireless communication systems may employ multiple-access radio access technologies (RATs) capable of supporting communication with multiple users by sharing available system resources (for example, time domain resources, frequency domain resources, spatial domain resources, and/or device transmit power, among other examples) . Examples of such multiple-access RATs include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, and time division synchronous code division multiple access (TD-SCDMA) systems.

The above multiple-access RATs have been adopted in various telecommunication standards to provide common protocols that enable different wireless communication devices to communicate on a municipal, national, regional, or global level. An example telecommunication standard is New Radio (NR) . NR, which may also be referred to as 5G, is part of a continuous mobile broadband evolution promulgated by the Third Generation Partnership Project (3GPP) . NR (and other mobile broadband evolutions beyond NR) may be designed to better support Internet of things (IoT) and reduced capability device deployments, industrial connectivity, millimeter wave (mmWave) expansion, licensed and unlicensed spectrum access, non-terrestrial network (NTN) deployment, sidelink and other device-to-device direct communication technologies (for example, cellular vehicle-to-everything (CV2X) communication) , massive multiple-input multiple-output (MIMO) , disaggregated network architectures and network topology expansions, multiple-subscriber implementations, high-precision positioning, and/or radio frequency (RF) sensing, among other examples. As the demand for mobile broadband access continues to increase, further improvements in NR may be implemented, and other radio access technologies such as 6G may be introduced, to further advance mobile broadband evolution.

SUMMARY

Some aspects described herein relate to a method of wireless communication performed at a user equipment (UE) . The method may include receiving entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF. The method may include transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to a method of wireless communication performed at a UE. The method may include receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The method may include transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to a method of wireless communication performed at a UE. The method may include receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The method may include transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to a method of wireless communication performed at a network node. The method may include transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF. The method may include receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to a method of wireless communication performed at a network node. The method may include transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The method may include receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to a method of wireless communication performed at a network node. The method may include transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The method may include receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the UE to receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF. The one or more processors may be configured to cause the UE to transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the UE to receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The one or more processors may be configured to cause the UE to transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the UE to receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The one or more processors may be configured to cause the UE to transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to an apparatus for wireless communication at a network node. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the network node to transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF. The one or more processors may be configured to cause the network node to receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to an apparatus for wireless communication at a network node. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the network node to transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The one or more processors may be configured to cause the network node to receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to an apparatus for wireless communication at a network node. The apparatus may include one or more memories and one or more processors coupled with the one or more memories. The one or more processors may be configured to cause the network node to transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The one or more processors may be configured to cause the network node to receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a UE. The set of instructions, when executed by one or more processors of the UE, may cause the UE to receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The set of instructions, when executed by one or more processors of the UE, may cause the UE to transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a network node. The set of instructions, when executed by one or more processors of the network node, may cause the network node to transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF. The set of instructions, when executed by one or more processors of the network node, may cause the network node to receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a network node. The set of instructions, when executed by one or more processors of the network node, may cause the network node to transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The set of instructions, when executed by one or more processors of the network node, may cause the network node to receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to a non-transitory computer-readable medium that stores a set of instructions for wireless communication by a network node. The set of instructions, when executed by one or more processors of the network node, may cause the network node to transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The set of instructions, when executed by one or more processors of the network node, may cause the network node to receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF. The apparatus may include means for transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The apparatus may include means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The apparatus may include means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF. The apparatus may include means for receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The apparatus may include means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include means for transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The apparatus may include means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Aspects of the present disclosure may generally be implemented by or as a method, apparatus, system, computer program product, non-transitory computer-readable medium, user equipment, base station, network node, network entity, wireless communication device, and/or processing system as substantially described with reference to, and as illustrated by, the specification and accompanying drawings.

The foregoing paragraphs of this section have broadly summarized some aspects of the present disclosure. These and additional aspects will be described hereinafter. The disclosed aspects may be used as a basis for modifying or designing other aspects for carrying out the same or similar purposes of the present disclosure. Such equivalent aspects do not depart from the scope of the appended claims. Characteristics of the aspects disclosed herein, both their organization and method of operation will be better understood from the following description when considered in connection with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The appended drawings illustrate some aspects of the present disclosure, but are not limiting of the scope of the present disclosure because the description may enable other aspects. Each of the drawings is provided for purposes of illustration and description, and not as a definition of the limits of the claims. The same or similar reference numbers in different drawings may identify the same or similar elements.

Fig. 1 is a diagram illustrating an example of a wireless communication network in accordance with the present disclosure.

Fig. 2 is a diagram illustrating an example network node in communication with an example UE in a wireless network in accordance with the present disclosure.

Fig. 3 is a diagram illustrating an example disaggregated base station architecture in accordance with the present disclosure.

Figs. 4A and 4B are diagrams illustrating an example of data compression for channel state feedback, in accordance with the present disclosure.

Figs. 5A and 5B are diagrams illustrating an example of data compression using vector quantization and entropy coding, in accordance with the present disclosure.

Figs. 6A-6F are diagrams illustrating an example associated with configuration of entropy coding for channel state feedback, in accordance with the present disclosure.

Figs. 7-9 are diagrams illustrating an example process performed, for example, at a user equipment (UE) or an apparatus of a UE, in accordance with the present disclosure.

Figs. 10-12 are diagrams illustrating example processes performed, for example, at a network node or an apparatus of a network node, in accordance with the present disclosure.

Fig. 13 is a diagram of an example apparatus for wireless communication, in accordance with the present disclosure.

Fig. 14 is a diagram illustrating an example of a hardware implementation for an apparatus employing a processing system, in accordance with the present disclosure.

Figs. 15-17 are diagram illustrating examples of implementations of code and circuitry for one or more apparatuses, in accordance with the present disclosure.

Fig. 18 is a diagram of an example apparatus for wireless communication, in accordance with the present disclosure.

Fig. 19 is a diagram illustrating an example of a hardware implementation for an apparatus employing a processing system, in accordance with the present disclosure.

Figs. 20-22 are diagram illustrating examples of implementations of code and circuitry for one or more apparatuses, in accordance with the present disclosure.

DETAILED DESCRIPTION

In a wireless communication system, a network node may transmit a channel state information (CSI) reference signal (CSI-RS) to a user equipment (UE) , which may perform a measurement of the CSI-RS. For example, the UE may measure a received power of the CSI-RS (which may take the form of a reference signal received power (RSRP) parameter) , a received quality of the CSI-RS (which may take the form of a reference signal received quality (RSRQ) parameter) , or a signal to interference and noise (SINR) of the CSI-RS (which may take the form of a SINR parameter) , among other examples. The UE may estimate a downlink channel response using the measurements of the CSI-RS and may report a set of CSI indicators to the network node. The set of CSI indicators may include a rank indicator (RI) , a precoding matrix indicator (PMI) , or a channel quality indicator (CQI) , among other examples. The network node may use the set of CSI indicators, which may collectively form a channel state feedback (CSF) message to configure subsequent transmissions on the downlink channel, such as by configuring a target code rate, a modulation type, a quantity of transmission layers, or a precoding matrix, among other examples. By estimating a downlink channel at the UE, reporting the estimate of the downlink channel to the network node, and configuring transmissions on the downlink channel at the network node, the UE and the network node can achieve efficient communication.

One improvement to the downlink channel estimation procedure is to use data compression techniques to reduce an amount of overhead associated with transmitting the CSF. For example, a UE may process a downlink channel estimate to reduce an amount of CSI feedback data that the UE transmits to the network node. The UE processing may be a form of encoding. Correspondingly, the network node may receive the CSI feedback data and process the data-compressed CSI feedback data to recover a downlink channel estimate from the data-compressed CSI feedback data. The network node processing may be a form of decoding. In one data compression technique, the UE uses a codebook, which is a set of code words representing possible PMI values, to select a best PMI code word, which represents a best determined PMI value. The UE transmits a sequence of bits to report the best PMI code word, and the network node recovers the best PMI code word and corresponding PMI value from the sequence of bits.

Artificial intelligence (AI) -based CSI feedback is another data compression technique that the UE may use. To perform AI-based CSI feedback, the UE may perform a vector quantization (VQ) procedure in which values of the CSI feedback data are divided into vectors, and the vectors are aligned to a set of code words of a quantization codebook. This reduces the CSF message data, which may include values of CSI feedback data or derived from CSI feedback data, to a group of code words, which may correspond to discrete binary values.

Another technique the UE may perform for data compression is entropy coding. Entropy coding is a statistical data compression technique in which lossless data compression can be achieved using statistical mapping of values in an underlying dataset to values that represent the underlying dataset. In performing entropy coding, which may be referred to as “EC, ” the UE estimates a probability matrix function (PMF) of a random variable and generates a variable length codeword as an output using the PMF. The PMF is a discrete random variable over a space {0, …, K-1} that is non-uniform and is dependent on which AI model is used for the encoder and a probability distribution of an input dataset (hyper-local datasets correspond to different PMFs) . Accordingly, to achieve data compression for AI-based CSI feedback, the UE may perform an entropy coding technique to compress sequences of bits, from which the UE generates symbols, associated with the quantization of the CSF message data. By performing data compression on CSF message data, the UE reduces overhead in transmitting sequences of symbols, such as occurs when transmitting CSF messages. By using entropy coding, as described below, for achieving data compression, the UE achieves lossless data compression, thereby ensuring that a network node can generate a communication configuration for a channel using the CSF message.

In one version of entropy coding, referred to as “Huffman coding” , the UE generates a lookup table of bit sequences corresponding to input symbols that the UE is to transmit (the input symbols correspond to sequences of bits from the VQ procedure) . The UE maps the input symbols that the UE is to transmit to bit sequences using the lookup table and transmits the bit sequences, rather than the input symbols. The lookup table of bit sequences is ordered by frequency, with smaller bit sequences representing more frequently used symbols. The UE may derive the lookup table using a code word tree in which a position of input symbols within the code word tree corresponds to a frequency of the input symbols within the CSF message data. Accordingly, the UE may map the most frequently used symbols to smaller bit sequences (and less frequently used symbols to larger bit sequences) , thereby achieving data compression for transmission. A network node may reverse the mapping of symbols to bit sequences to recover the CSF message data. For example, in entropy decoding for Huffman coding, the network node may receive a plurality of bit sequences, map the bit sequences to symbols using a lookup table, and decode the plurality of bit sequences into the symbols using the mapping.

In another version of entropy coding, referred to as “Arithmetic coding” , the UE encodes an entire message of multiple symbols into a single number with a finite precision corresponding to a quantity of bits that represent the single number. For example, each digit of the single number may correspond to a different symbol of CSF message data, using an arithmetic algorithm. The single number may be a fraction within a configured range of numbers. By using the arithmetic algorithm, the UE encodes more frequently used symbols with fewer bits and less frequently used symbols with more bits, resulting in fewer bits being used in total, thereby achieving data compression. The UE may transmit an output sequence representing the single number to convey the CSF message data. In a corresponding entropy decoding procedure for Arithmetic coding, the network node may use the arithmetic algorithm to parse the single number and recover the symbols of the CSF message data.

Combining vector quantization and entropy coding, a UE may quantize an output of an encoder (alatent vector Z) using vector quantization, such that Z is mapped to an embedding vector Z_embd (with entries from {0, …, K-1} , where K is a codebook size) . Entropy coding can be applied to further compress the output of the encoder. This results in a generated CSF report that can be transmitted to the network node with reduced data size relative to an uncompressed CSF report. On a decoder side, the network node receives the generated CSF report and performs entropy decoding. Using a result of performing entropy decoding, the network node performs vector de-quantization to recover the CSF message data. The network node may use the recovered CSF message data to configure one or more channel parameters for subsequent communication.

When the network node performs the above-mentioned procedures for decoding and recovering the CSF message, the network node may use one or more parameters or configurations to successfully obtain CSF message data from an encoded, compressed CSF message. For example, the network node may use information indicating which version of entropy coding has been used to determine whether to use a lookup table, as in Huffman coding, or an arithmetic algorithm, as in Arithmetic coding, to convert a set of bits to a set of symbols from which the CSF message can be recovered. Similarly, to reverse an entropy coding procedure, the network node may use an estimate of a probability mass function (PMF) that the UE used to derive a code word tree, as in Huffman coding, or as a parameter of the arithmetic algorithm, as in Arithmetic coding. There may be many other implementation-specific or otherwise specified parameters that the UE uses in encoding CSF message data, which the network node uses is decoding CSF message data.

When an encoder of the UE is not synchronized with a decoder of the network node-in other words, when the network node does not have information identifying the parameters used by the UE for encoding-the network node may be unsuccessful or inaccurate at recovering the CSF message data. Accordingly, when the network node attempts to configure downlink transmissions using the CSF message data, which has been recovered unsuccessfully or inaccurately, the network node may select parameters for the downlink transmissions that result in a less efficient usage of channel resources and/or that result in communication interruptions.

Various aspects relate generally to configuring entropy coding for CSF messages. Some aspects relate to a network node conveying, to a UE, information identifying a configuration of an AI-based CSF report. For example, the network node may transmit radio resource control (RRC) signaling identifying a type of entropy coding that the UE is to perform or a PMF parameter for an entropy coding procedure. In some aspects, the network node may transmit RRC signaling indicating whether the UE is to apply entropy coding as multiple entropy coding procedures for multiple layers of VQ output, which may be the CSF message data, or whether the UE is to merge the multiple layers of VQ output and perform a single entropy coding procedure for the merged VQ output. In some aspects, the network node may indicate whether the UE is to transmit an indication of one or more parameters used for entropy coding along with transmitting an entropy coded message. For example, the network node may instruct the UE to transmit an indication of a length of an entropy coding output, which the network node can use for decoding.

In some aspects, the network node may transmit an indication of whether to activate or deactivate entropy coding. For example, the UE may have the capability to adaptively use entropy coding or switch to using another technique, and the network node may transmit an indication of which technique to use at which time. In some aspects, the network node may transmit an indication of a maximum payload size for a CSI report. For example, the network node may configure the UE such that when the UE determines that the maximum payload size is exceeded, the UE may be configured to switch from using entropy coding to not using entropy coding. In some aspects, the network node may transmit an indication of a payload structure for a CSF message encoded using entropy coding. For example, the network node may indicate that the UE is to transmit a first type of message with a first format or a second type of message with a second format. In this example, the first format may have a first set of fields for the UE to convey a configuration used for entropy coding (EC coding) , and the second format may have a second set of fields for the UE to convey the configuration used for EC coding. Examples of the types of fields may include a field for identifying a length of an entropy coding output or whether entropy coding has been bypassed.

Particular aspects of the subject matter described in this disclosure can be implemented to realize one or more of the following potential improvements. In some examples, by the network node transmitting configuration information, the described techniques can be used to synchronize an encoder of the UE with a decoder of the network node. By synchronizing the encoder of the UE with the decoder of the network node, the UE and the network node may perform lossless entropy coding and decoding. In some examples, by the UE transmitting a CSF message with a configured payload, which includes one or more parameters associated with entropy coding, the described techniques can be used to ensure that the decoder of the network node is synchronized with the encoder of the UE. In some examples, by synchronizing a decoder of the network node with an encoder of the UE, the described techniques can be used to successfully recover CSF feedback at the network node and configure subsequent transmissions on a downlink channel for efficient utilization of channel resources. In some examples, by the network node transmitting configuration information and/or by the UE transmitting a CSF message with a configured payload, the described techniques can be used to allow successful entropy coding and decoding of CSF feedback, which reduces overhead associated with CSF message transmission. In some examples, by the network node and/or the UE reducing overhead, the network node and/or the UE make channel resources available for other communications.

Various aspects of the present disclosure are described hereinafter with reference to the accompanying drawings. However, aspects of the present disclosure may be embodied in many different forms and is not to be construed as limited to any specific aspect illustrated by or described with reference to an accompanying drawing or otherwise presented in this disclosure. Rather, these aspects are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. One skilled in the art may appreciate that the scope of the disclosure is intended to cover any aspect of the disclosure disclosed herein, whether implemented independently of or in combination with any other aspect of the disclosure. For example, an apparatus may be implemented or a method may be practiced using various combinations or quantities of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover an apparatus having, or a method that is practiced using, other structures and/or functionalities in addition to or other than the structures and/or functionalities with which various aspects of the disclosure set forth herein may be practiced. Any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim.

Several aspects of telecommunication systems will now be presented with reference to various methods, operations, apparatuses, and techniques. These methods, operations, apparatuses, and techniques will be described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, components, circuits, steps, processes, or algorithms (collectively referred to as “elements” ) . These elements may be implemented using hardware, software, or a combination of hardware and software. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.

Multiple-access radio access technologies (RATs) have been adopted in various telecommunication standards to provide common protocols that enable wireless communication devices to communicate on a municipal, enterprise, national, regional, or global level. For example, 5G New Radio (NR) is part of a continuous mobile broadband evolution promulgated by the Third Generation Partnership Project (3GPP) . 5G NR supports various technologies and use cases including enhanced mobile broadband (eMBB) , ultra-reliable low-latency communication (URLLC) , massive machine-type communication (mMTC) , millimeter wave (mmWave) technology, beamforming, network slicing, edge computing, Internet of Things (IoT) connectivity and management, and network function virtualization (NFV) .

As the demand for broadband access increases and as technologies supported by wireless communication networks evolve, further technological improvements may be adopted in or implemented for 5G NR or future RATs, such as 6G, to further advance the evolution of wireless communication for a wide variety of existing and new use cases and applications. Such technological improvements may be associated with new frequency band expansion, licensed and unlicensed spectrum access, overlapping spectrum use, small cell deployments, non-terrestrial network (NTN) deployments, disaggregated network architectures and network topology expansion, device aggregation, advanced duplex communication, sidelink and other device-to-device direct communication, IoT (including passive or ambient IoT) networks, reduced capability (RedCap) UE functionality, industrial connectivity, multiple-subscriber implementations, high-precision positioning, radio frequency (RF) sensing, and/or artificial intelligence or machine learning (AI/ML) , among other examples. These technological improvements may support use cases such as wireless backhauls, wireless data centers, extended reality (XR) and metaverse applications, meta services for supporting vehicle connectivity, holographic and mixed reality communication, autonomous and collaborative robots, vehicle platooning and cooperative maneuvering, sensing networks, gesture monitoring, human-brain interfacing, digital twin applications, asset management, and universal coverage applications using non-terrestrial and/or aerial platforms, among other examples. The methods, operations, apparatuses, and techniques described herein may enable one or more of the foregoing technologies and/or support one or more of the foregoing use cases.

Fig. 1 is a diagram illustrating an example of a wireless communication network 100 in accordance with the present disclosure. The wireless communication network 100 may be or may include elements of a 5G (or NR) network or a 6G network, among other examples. The wireless communication network 100 may include multiple network nodes 110, shown as a network node (NN) 110a, a network node 110b, a network node 110c, and a network node 110d. The network nodes 110 may support communications with multiple UEs 120, shown as a UE 120a, a UE 120b, a UE 120c, a UE 120d, and a UE 120e.

The network nodes 110 and the UEs 120 of the wireless communication network 100 may communicate using the electromagnetic spectrum, which may be subdivided by frequency or wavelength into various classes, bands, carriers, and/or channels. For example, devices of the wireless communication network 100 may communicate using one or more operating bands. In some aspects, multiple wireless networks 100 may be deployed in a given geographic area. Each wireless communication network 100 may support a particular RAT (which may also be referred to as an air interface) and may operate on one or more carrier frequencies in one or more frequency ranges. Examples of RATs include a 4G RAT, a 5G/NR RAT, and/or a 6G RAT, among other examples. In some examples, when multiple RATs are deployed in a given geographic area, each RAT in the geographic area may operate on different frequencies to avoid interference with one another.

Various operating bands have been defined as frequency range designations FR1 (410 MHz through 7.125 GHz) , FR2 (24.25 GHz through 52.6 GHz) , FR3 (7.125 GHz through 24.25 GHz) , FR4a or FR4-1 (52.6 GHz through 71 GHz) , FR4 (52.6 GHz through 114.25 GHz) , and FR5 (114.25 GHz through 300 GHz) . Although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as a “Sub-6 GHz” band in some documents and articles. Similarly, FR2 is often referred to(interchangeably) as a “millimeter wave” band in some documents and articles, despite being different than the extremely high frequency (EHF) band (30 GHz through 300 GHz) , which is identified by the International Telecommunications Union (ITU) as a “millimeter wave” band. The frequencies between FR1 and FR2 are often referred to as mid-band frequencies, which include FR3. Frequency bands falling within FR3 may inherit FR1 characteristics or FR2 characteristics, and thus may effectively extend features of FR1 or FR2 into mid-band frequencies. Thus, “sub-6 GHz, ” if used herein, may broadly refer to frequencies that are less than 6 GHz, that are within FR1, and/or that are included in mid-band frequencies. Similarly, the term “millimeter wave, ” if used herein, may broadly refer to frequencies that are included in mid-band frequencies, that are within FR2, FR4, FR4-aor FR4-1, or FR5, and/or that are within the EHF band. Higher frequency bands may extend 5G NR operation, 6G operation, and/or other RATs beyond 52.6 GHz. For example, each of FR4a, FR4-1, FR4, and FR5 falls within the EHF band. In some examples, the wireless communication network 100 may implement dynamic spectrum sharing (DSS) , in which multiple RATs (for example, 4G/LTE and 5G/NR) are implemented with dynamic bandwidth allocation (for example, based on user demand) in a single frequency band. It is contemplated that the frequencies included in these operating bands (for example, FR1, FR2, FR3, FR4, FR4-a, FR4-1, and/or FR5) may be modified, and techniques described herein may be applicable to those modified frequency ranges.

A network node 110 may include one or more devices, components, or systems that enable communication between a UE 120 and one or more devices, components, or systems of the wireless communication network 100. A network node 110 may be, may include, or may also be referred to as an NR network node, a 5G network node, a 6G network node, a Node B, an eNB, a gNB, an access point (AP) , a transmission reception point (TRP) , a mobility element, a core, a network entity, a network element, a network equipment, and/or another type of device, component, or system included in a radio access network (RAN) .

A network node 110 may be implemented as a single physical node (for example, a single physical structure) or may be implemented as two or more physical nodes (for example, two or more distinct physical structures) . For example, a network node 110 may be a device or system that implements part of a radio protocol stack, a device or system that implements a full radio protocol stack (such as a full gNB protocol stack) , or a collection of devices or systems that collectively implement the full radio protocol stack. For example, and as shown, a network node 110 may be an aggregated network node (having an aggregated architecture) , meaning that the network node 110 may implement a full radio protocol stack that is physically and logically integrated within a single node (for example, a single physical structure) in the wireless communication network 100. For example, an aggregated network node 110 may consist of a single standalone base station or a single TRP that uses a full radio protocol stack to enable or facilitate communication between a UE 120 and a core network of the wireless communication network 100.

Alternatively, and as also shown, a network node 110 may be a disaggregated network node (sometimes referred to as a disaggregated base station) , meaning that the network node 110 may implement a radio protocol stack that is physically distributed and/or logically distributed among two or more nodes in the same geographic location or in different geographic locations. For example, a disaggregated network node may have a disaggregated architecture. In some deployments, disaggregated network nodes 110 may be used in an integrated access and backhaul (IAB) network, in an open radio access network (O-RAN) (such as a network configuration in compliance with the O-RAN Alliance) , or in a virtualized radio access network (vRAN) , also known as a cloud radio access network (C-RAN) , to facilitate scaling by separating base station functionality into multiple units that can be individually deployed.

The network nodes 110 of the wireless communication network 100 may include one or more central units (CUs) , one or more distributed units (DUs) , and/or one or more radio units (RUs) . A CU may host one or more higher layer control functions, such as RRC functions, packet data convergence protocol (PDCP) functions, and/or service data adaptation protocol (SDAP) functions, among other examples. A DU may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and/or one or more higher physical (PHY) layers depending, at least in part, on a functional split, such as a functional split defined by the 3GPP. In some examples, a DU also may host one or more lower PHY layer functions, such as a fast Fourier transform (FFT) , an inverse FFT (iFFT) , beamforming, physical random access channel (PRACH) extraction and filtering, and/or scheduling of resources for one or more UEs 120, among other examples. An RU may host RF processing functions or lower PHY layer functions, such as an FFT, an iFFT, beamforming, or PRACH extraction and filtering, among other examples, according to a functional split, such as a lower layer functional split. In such an architecture, each RU can be operated to handle over the air (OTA) communication with one or more UEs 120.

In some aspects, a single network node 110 may include a combination of one or more CUs, one or more DUs, and/or one or more RUs. Additionally or alternatively, a network node 110 may include one or more Near-Real Time (Near-RT) RAN Intelligent Controllers (RICs) and/or one or more Non-Real Time (Non-RT) RICs. In some examples, a CU, a DU, and/or an RU may be implemented as a virtual unit, such as a virtual central unit (VCU) , a virtual distributed unit (VDU) , or a virtual radio unit (VRU) , among other examples. A virtual unit may be implemented as a virtual network function, such as associated with a cloud deployment.

Some network nodes 110 (for example, a base station, an RU, or a TRP) may provide communication coverage for a particular geographic area. In the 3GPP, the term “cell” can refer to a coverage area of a network node 110 or to a network node 110 itself, depending on the context in which the term is used. A network node 110 may support one or multiple (for example, three) cells. In some examples, a network node 110 may provide communication coverage for a macro cell, a pico cell, a femto cell, or another type of cell. A macro cell may cover a relatively large geographic area (for example, several kilometers in radius) and may allow unrestricted access by UEs 120 with service subscriptions. A pico cell may cover a relatively small geographic area and may allow unrestricted access by UEs 120 with service subscriptions. A femto cell may cover a relatively small geographic area (for example, a home) and may allow restricted access by UEs 120 having association with the femto cell (for example, UEs 120 in a closed subscriber group (CSG) ) . A network node 110 for a macro cell may be referred to as a macro network node. A network node 110 for a pico cell may be referred to as a pico network node. A network node 110 for a femto cell may be referred to as a femto network node or an in-home network node. In some examples, a cell may not necessarily be stationary. For example, the geographic area of the cell may move according to the location of an associated mobile network node 110 (for example, a train, a satellite base station, an unmanned aerial vehicle, or a non-terrestrial network (NTN) network node) .

The wireless communication network 100 may be a heterogeneous network that includes network nodes 110 of different types, such as macro network nodes, pico network nodes, femto network nodes, relay network nodes, aggregated network nodes, and/or disaggregated network nodes, among other examples. In the example shown in Fig. 1, the network node 110a may be a macro network node for a macro cell 130a, the network node 110b may be a pico network node for a pico cell 130b, and the network node 110c may be a femto network node for a femto cell 130c. Various different types of network nodes 110 may generally transmit at different power levels, serve different coverage areas, and/or have different impacts on interference in the wireless communication network 100 than other types of network nodes 110. For example, macro network nodes may have a high transmit power level (for example, 5 to 40 watts) , whereas pico network nodes, femto network nodes, and relay network nodes may have lower transmit power levels (for example, 0.1 to 2 watts) .

In some examples, a network node 110 may be, may include, or may operate as an RU, a TRP, or a base station that communicates with one or more UEs 120 via a radio access link (which may be referred to as a “Uu” link) . The radio access link may include a downlink and an uplink. “Downlink” (or “DL” ) refers to a communication direction from a network node 110 to a UE 120, and “uplink” (or “UL” ) refers to a communication direction from a UE 120 to a network node 110. Downlink channels may include one or more control channels and one or more data channels. A downlink control channel may be used to transmit downlink control information (DCI) (for example, scheduling information, reference signals, and/or configuration information) from a network node 110 to a UE 120. A downlink data channel may be used to transmit downlink data (for example, user data associated with a UE 120) from a network node 110 to a UE 120. Downlink control channels may include one or more physical downlink control channels (PDCCHs) , and downlink data channels may include one or more physical downlink shared channels (PDSCHs) . Uplink channels may similarly include one or more control channels and one or more data channels. An uplink control channel may be used to transmit uplink control information (UCI) (for example, reference signals and/or feedback corresponding to one or more downlink transmissions) from a UE 120 to a network node 110. An uplink data channel may be used to transmit uplink data (for example, user data associated with a UE 120) from a UE 120 to a network node 110. Uplink control channels may include one or more physical uplink control channels (PUCCHs) , and uplink data channels may include one or more physical uplink shared channels (PUSCHs) . The downlink and the uplink may each include a set of resources on which the network node 110 and the UE 120 may communicate.

Downlink and uplink resources may include time domain resources (frames, subframes, slots, and/or symbols) , frequency domain resources (frequency bands, component carriers, subcarriers, resource blocks, and/or resource elements) , and/or spatial domain resources (particular transmit directions and/or beam parameters) . Frequency domain resources of some bands may be subdivided into bandwidth parts (BWPs) . A BWP may be a continuous block of frequency domain resources (for example, a continuous block of resource blocks) that are allocated for one or more UEs 120. A UE 120 may be configured with both an uplink BWP and a downlink BWP (where the uplink BWP and the downlink BWP may be the same BWP or different BWPs) . A BWP may be dynamically configured (for example, by a network node 110 transmitting a DCI configuration to the one or more UEs 120) and/or reconfigured, which means that a BWP can be adjusted in real-time (or near-real-time) based on changing network conditions in the wireless communication network 100 and/or based on the specific requirements of the one or more UEs 120. This enables more efficient use of the available frequency domain resources in the wireless communication network 100 because fewer frequency domain resources may be allocated to a BWP for a UE 120 (which may reduce the quantity of frequency domain resources that a UE 120 is required to monitor) , leaving more frequency domain resources to be spread across multiple UEs 120. Thus, BWPs may also assist in the implementation of lower-capability UEs 120 by facilitating the configuration of smaller bandwidths for communication by such UEs 120.

As described above, in some aspects, the wireless communication network 100 may be, may include, or may be included in, an IAB network. In an IAB network, at least one network node 110 is an anchor network node that communicates with a core network. An anchor network node 110 may also be referred to as an IAB donor (or “IAB-donor” ) . The anchor network node 110 may connect to the core network via a wired backhaul link. For example, an Ng interface of the anchor network node 110 may terminate at the core network. Additionally or alternatively, an anchor network node 110 may connect to one or more devices of the core network that provide a core access and mobility management function (AMF) . An IAB network also generally includes multiple non-anchor network nodes 110, which may also be referred to as relay network nodes or simply as IAB nodes (or “IAB-nodes” ) . Each non-anchor network node 110 may communicate directly with the anchor network node 110 via a wireless backhaul link to access the core network, or may communicate indirectly with the anchor network node 110 via one or more other non-anchor network nodes 110 and associated wireless backhaul links that form a backhaul path to the core network. Some anchor network node 110 or other non-anchor network node 110 may also communicate directly with one or more UEs 120 via wireless access links that carry access traffic. In some examples, network resources for wireless communication (such as time resources, frequency resources, and/or spatial resources) may be shared between access links and backhaul links.

In some examples, any network node 110 that relays communications may be referred to as a relay network node, a relay station, or simply as a relay. A relay may receive a transmission of a communication from an upstream station (for example, another network node 110 or a UE 120) and transmit the communication to a downstream station (for example, a UE 120 or another network node 110) . The wireless communication network 100 may include or be referred to as a “multi-hop network. ” In the example shown in Fig. 1, the network node 110d (for example, a relay network node) may communicate with the network node 110a (for example, a macro network node) and the UE 120d in order to facilitate communication between the network node 110a and the UE 120d. Additionally or alternatively, a UE 120 may be or may operate as a relay station that can relay transmissions to or from other UEs 120. A UE 120 that relays communications may be referred to as a UE relay or a relay UE, among other examples.

The UEs 120 may be physically dispersed throughout the wireless communication network 100, and each UE 120 may be stationary or mobile. A UE 120 may be, may include, or may be included in an access terminal, another terminal, a mobile station, or a subscriber unit. A UE 120 may be, include, or be coupled with a cellular phone (for example, a smart phone) , a personal digital assistant (PDA) , a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device, a biometric device, a wearable device (for example, a smart watch, smart clothing, smart glasses, a smart wristband, and/or smart jewelry, such as a smart ring or a smart bracelet) , an entertainment device (for example, a music device, a video device, and/or a satellite radio) , an extended reality (XR) device, a vehicular component or sensor, a smart meter or sensor, industrial manufacturing equipment, a Global Navigation Satellite System (GNSS) device (such as a Global Positioning System device or another type of positioning device) , a UE function of a network node, and/or any other suitable device or function that may communicate via a wireless medium.

A UE 120 and/or a network node 110 may include one or more chips, system-on-chips (SoCs) , chipsets, packages, or devices that individually or collectively constitute or comprise a processing system. The processing system includes processor (or “processing” ) circuitry in the form of one or multiple processors, microprocessors, processing units (such as central processing units (CPUs) , graphics processing units (GPUs) , neural processing units (NPUs) and/or digital signal processors (DSPs) ) , processing blocks, application-specific integrated circuits (ASIC) , programmable logic devices (PLDs) (such as field programmable gate arrays (FPGAs) ) , or other discrete gate or transistor logic or circuitry (all of which may be generally referred to herein individually as “processors” or collectively as “the processor” or “the processor circuitry” ) .. A processor also may be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. One or more of the processors may be individually or collectively configurable or configured to perform various functions or operations described herein. A group of processors collectively configurable or configured to perform a set of functions may include a first processor configurable or configured to perform a first function of the set and a second processor configurable or configured to perform a second function of the set, or may include the group of processors all being configured or configurable to perform the set of functions.

The processing system may further include memory circuitry in the form of one or more memory devices, memory blocks, memory elements or other discrete gate or transistor logic or circuitry, each of which may include tangible storage media such as random-access memory (RAM) or read-only memory (ROM) , or combinations thereof (all of which may be generally referred to herein individually as “memories” or collectively as “the memory” or “the memory circuitry” ) . One or more of the memories may be coupled (for example, operatively coupled, communicatively coupled, electronically coupled, or electrically coupled) with one or more of the processors and may individually or collectively store processor-executable code (such as software) that, when executed by one or more of the processors, may configure one or more of the processors to perform various functions or operations described herein. Additionally or alternatively, in some examples, one or more of the processors may be preconfigured to perform various functions or operations described herein without requiring configuration by software. The processing system may further include or be coupled with one or more modems (such as a Wi-Fi (for example, IEEE compliant) modem or a cellular (for example, 3GPP 4G LTE, 5G, or 6G compliant) modem) . In some implementations, one or more processors of the processing system include or implement one or more of the modems. The processing system may further include or be coupled with multiple radios (collectively “the radio” ) , multiple RF chains, or multiple transceivers, each of which may in turn be coupled with one or more of multiple antennas. In some implementations, one or more processors of the processing system include or implement one or more of the radios, RF chains or transceivers. The UE 120 may include or may be included in a housing that houses components associated with the UE 120 including the processing system.

Some UEs 120 may be considered machine-type communication (MTC) UEs, evolved or enhanced machine-type communication (eMTC) , UEs, further enhanced eMTC (feMTC) UEs, or enhanced feMTC (efeMTC) UEs, or further evolutions thereof, all of which may be simply referred to as “MTC UEs” . An MTC UE may be, may include, or may be included in or coupled with a robot, an unmanned aerial vehicle or drone, a remote device, a sensor, a meter, a monitor, and/or a location tag. Some UEs 120 may be considered IoT devices and/or may be implemented as NB-IoT (narrowband IoT) devices. An IoT UE or NB-IoT device may be, may include, or may be included in or coupled with an industrial machine, an appliance, a refrigerator, a doorbell camera device, a home automation device, and/or a light fixture, among other examples. Some UEs 120 may be considered Customer Premises Equipment, which may include telecommunications devices that are installed at a customer location (such as a home or office) to enable access to a service provider's network (such as included in or in communication with the wireless communication network 100) .

Some UEs 120 may be classified according to different categories in association with different complexities and/or different capabilities. UEs 120 in a first category may facilitate massive IoT in the wireless communication network 100, and may offer low complexity and/or cost relative to UEs 120 in a second category. UEs 120 in a second category may include mission-critical IoT devices, legacy UEs, baseline UEs, high-tier UEs, advanced UEs, full-capability UEs, and/or premium UEs that are capable of ultra-reliable low-latency communication (URLLC) , enhanced mobile broadband (eMBB) , and/or precise positioning in the wireless communication network 100, among other examples. A third category of UEs 120 may have mid-tier complexity and/or capability (for example, a capability between UEs 120 of the first category and UEs 120 of the second capability) . A UE 120 of the third category may be referred to as a reduced capacity UE ( “RedCap UE” ) , a mid-tier UE, an NR-Light UE, and/or an NR-Lite UE, among other examples. RedCap UEs may bridge a gap between the capability and complexity of NB-IoT devices and/or eMTC UEs, and mission-critical IoT devices and/or premium UEs. RedCap UEs may include, for example, wearable devices, IoT devices, industrial sensors, and/or cameras that are associated with a limited bandwidth, power capacity, and/or transmission range, among other examples. RedCap UEs may support healthcare environments, building automation, electrical distribution, process automation, transport and logistics, and/or smart city deployments, among other examples.

In some examples, two or more UEs 120 (for example, shown as UE 120a and UE 120e) may communicate directly with one another using sidelink communications (for example, without communicating by way of a network node 110 as an intermediary) . As an example, the UE 120a may directly transmit data, control information, or other signaling as a sidelink communication to the UE 120e. This is in contrast to, for example, the UE 120a first transmitting data in an UL communication to a network node 110, which then transmits the data to the UE 120e in a DL communication. In various examples, the UEs 120 may transmit and receive sidelink communications using peer-to-peer (P2P) communication protocols, device-to-device (D2D) communication protocols, vehicle-to-everything (V2X) communication protocols (which may include vehicle-to-vehicle (V2V) protocols, vehicle-to-infrastructure (V2I) protocols, and/or vehicle-to-pedestrian (V2P) protocols) , and/or mesh network communication protocols. In some deployments and configurations, a network node 110 may schedule and/or allocate resources for sidelink communications between UEs 120 in the wireless communication network 100. In some other deployments and configurations, a UE 120 (instead of a network node 110) may perform, or collaborate or negotiate with one or more other UEs to perform, scheduling operations, resource selection operations, and/or other operations for sidelink communications.

In some examples, as shown by reference number 190, the UE 120a may receive configuration information or a CSI-RS from a network node 110a. For example, the UE 120a may receive configuration information that identifies a set of resources for receiving a CSI-RS and/or a configuration for a CSF message that is generated using a measurement of the CSI-RS. In some examples, as shown by reference number 192, the UE 120a may transmit the CSF message to the network node 110a. For example, the UE 120a may generate a CSF message and encode a content of the CSF message using a compression technique, such as vector quantization and/or entropy coding. In this example, the UE 120a transmits the CSF message to the network node 110a, which can decode the content of the CSF message to configure subsequent communications with the UE 120a.

In various examples, some of the network nodes 110 and the UEs 120 of the wireless communication network 100 may be configured for full-duplex operation in addition to half-duplex operation. A network node 110 or a UE 120 operating in a half-duplex mode may perform only one of transmission or reception during particular time resources, such as during particular slots, symbols, or other time periods. Half-duplex operation may involve time-division duplexing (TDD) , in which DL transmissions of the network node 110 and UL transmissions of the UE 120 do not occur in the same time resources (that is, the transmissions do not overlap in time) . In contrast, a network node 110 or a UE 120 operating in a full-duplex mode can transmit and receive communications concurrently (for example, in the same time resources) . By operating in a full-duplex mode, network nodes 110 and/or UEs 120 may generally increase the capacity of the network and the radio access link. In some examples, full-duplex operation may involve frequency-division duplexing (FDD) , in which DL transmissions of the network node 110 are performed in a first frequency band or on a first component carrier and transmissions of the UE 120 are performed in a second frequency band or on a second component carrier different than the first frequency band or the first component carrier, respectively. In some examples, full-duplex operation may be enabled for a UE 120 but not for a network node 110. For example, a UE 120 may simultaneously transmit an UL transmission to a first network node 110 and receive a DL transmission from a second network node 110 in the same time resources. In some other examples, full-duplex operation may be enabled for a network node 110 but not for a UE 120. For example, a network node 110 may simultaneously transmit a DL transmission to a first UE 120 and receive an UL transmission from a second UE 120 in the same time resources. In some other examples, full-duplex operation may be enabled for both a network node 110 and a UE 120.

In some examples, the UEs 120 and the network nodes 110 may perform MIMO communication. “MIMO” generally refers to transmitting or receiving multiple signals (such as multiple layers or multiple data streams) simultaneously over the same time and frequency resources. MIMO techniques generally exploit multipath propagation. MIMO may be implemented using various spatial processing or spatial multiplexing operations. In some examples, MIMO may support simultaneous transmission to multiple receivers, referred to as multi-user MIMO (MU-MIMO) . Some RATs may employ advanced MIMO techniques, such as mTRP operation (including redundant transmission or reception on multiple TRPs) , reciprocity in the time domain or the frequency domain, single-frequency-network (SFN) transmission, or non-coherent joint transmission (NC-JT) .

In some aspects, the UE 120 may include a communication manager 140. As described in more detail elsewhere herein, the communication manager 140 may receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF; and transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. Additionally, or alternatively, the communication manager 140 may receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters. Additionally, or alternatively, the communication manager 140 may receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters. Additionally, or alternatively, the communication manager 140 may perform one or more other operations described herein.

In some aspects, the network node 110 may include a communication manager 150. As described in more detail elsewhere herein, the communication manager 150 may transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF; and receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. Additionally, or alternatively, the communication manager 150 may transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters. Additionally, or alternatively, the communication manager 150 may transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters. Additionally, or alternatively, the communication manager 150 may perform one or more other operations described herein.

As indicated above, Fig. 1 is provided as an example. Other examples may differ from what is described with regard to Fig. 1.

Fig. 2 is a diagram illustrating an example network node 110 in communication with an example UE 120 in a wireless network in accordance with the present disclosure.

As shown in Fig. 2, the network node 110 may include a data source 212, a transmit processor 214, a transmit (TX) MIMO processor 216, a set of modems 232 (shown as 232a through 232t, where t ≥ 1) , a set of antennas 234 (shown as 234a through 234v, where v ≥ 1) , a MIMO detector 236, a receive processor 238, a data sink 239, a controller/processor 240, a memory 242, a communication unit 244, a scheduler 246, and/or a communication manager 150, among other examples. In some configurations, one or a combination of the antenna (s) 234, the modem (s) 232, the MIMO detector 236, the receive processor 238, the transmit processor 214, and/or the TX MIMO processor 216 may be included in a transceiver of the network node 110. The transceiver may be under control of and used by one or more processors, such as the controller/processor 240, and in some aspects in conjunction with processor-readable code stored in the memory 242, to perform aspects of the methods, processes, and/or operations described herein. In some aspects, the network node 110 may include one or more interfaces, communication components, and/or other components that facilitate communication with the UE 120 or another network node.

The terms “processor, ” “controller, ” or “controller/processor” may refer to one or more controllers and/or one or more processors. For example, reference to “a/the processor, ” “a/the controller/processor, ” or the like (in the singular) should be understood to refer to any one or more of the processors described in connection with Fig. 2, such as a single processor or a combination of multiple different processors. Reference to “one or more processors” should be understood to refer to any one or more of the processors described in connection with Fig. 2. For example, one or more processors of the network node 110 may include transmit processor 214, TX MIMO processor 216, MIMO detector 236, receive processor 238, and/or controller/processor 240. Similarly, one or more processors of the UE 120 may include MIMO detector 256, receive processor 258, transmit processor 264, TX MIMO processor 266, and/or controller/processor 280.

In some aspects, a single processor may perform all of the operations described as being performed by the one or more processors. In some aspects, a first set of (one or more) processors of the one or more processors may perform a first operation described as being performed by the one or more processors, and a second set of (one or more) processors of the one or more processors may perform a second operation described as being performed by the one or more processors. The first set of processors and the second set of processors may be the same set of processors or may be different sets of processors. Reference to “one or more memories” should be understood to refer to any one or more memories of a corresponding device, such as the memory described in connection with Fig. 2. For example, operation described as being performed by one or more memories can be performed by the same subset of the one or more memories or different subsets of the one or more memories.

For downlink communication from the network node 110 to the UE 120, the transmit processor 214 may receive data ( “downlink data” ) intended for the UE 120 (or a set of UEs that includes the UE 120) from the data source 212 (such as a data pipeline or a data queue) . In some examples, the transmit processor 214 may select one or more MCSs for the UE 120 in accordance with one or more CQIs received from the UE 120. The network node 110 may process the data (for example, including encoding the data) for transmission to the UE 120 on a downlink in accordance with the MCS (s) selected for the UE 120 to generate data symbols. The transmit processor 214 may process system information (for example, semi-static resource partitioning information (SRPI) ) and/or control information (for example, CQI requests, grants, and/or upper layer signaling) and provide overhead symbols and/or control symbols. The transmit processor 214 may generate reference symbols for reference signals (for example, a cell-specific reference signal (CRS) , a demodulation reference signal (DMRS) , or a CSI-RS) and/or synchronization signals (for example, a primary synchronization signal (PSS) or a secondary synchronization signals (SSS) ) .

The TX MIMO processor 216 may perform spatial processing (for example, precoding) on the data symbols, the control symbols, the overhead symbols, and/or the reference symbols, if applicable, and may provide a set of output symbol streams (for example, T output symbol streams) to the set of modems 232. For example, each output symbol stream may be provided to a respective modulator component (shown as MOD) of a modem 232. Each modem 232 may use the respective modulator component to process (for example, to modulate) a respective output symbol stream (for example, for orthogonal frequency division multiplexing (OFDM) ) to obtain an output sample stream. Each modem 232 may further use the respective modulator component to process (for example, convert to analog, amplify, filter, and/or upconvert) the output sample stream to obtain a time domain downlink signal. The modems 232a through 232t may together transmit a set of downlink signals (for example, T downlink signals) via the corresponding set of antennas 234.

A downlink signal may include a DCI communication, a MAC control element (MAC-CE) communication, an RRC communication, a downlink reference signal, or another type of downlink communication. Downlink signals may be transmitted on a PDCCH, a PDSCH, and/or on another downlink channel. A downlink signal may carry one or more transport blocks (TBs) of data. A TB may be a unit of data that is transmitted over an air interface in the wireless communication network 100. A data stream (for example, from the data source 212) may be encoded into multiple TBs for transmission over the air interface. The quantity of TBs used to carry the data associated with a particular data stream may be associated with a TB size common to the multiple TBs. The TB size may be based on or otherwise associated with radio channel conditions of the air interface, the MCS used for encoding the data, the downlink resources allocated for transmitting the data, and/or another parameter. In general, the larger the TB size, the greater the amount of data that can be transmitted in a single transmission, which reduces signaling overhead. However, larger TB sizes may be more prone to transmission and/or reception errors than smaller TB sizes, but such errors may be mitigated by more robust error correction techniques.

For uplink communication from the UE 120 to the network node 110, uplink signals from the UE 120 may be received by an antenna 234, may be processed by a modem 232 (for example, a demodulator component, shown as DEMOD, of a modem 232) , may be detected by the MIMO detector 236 (for example, a receive (Rx) MIMO processor) if applicable, and/or may be further processed by the receive processor 238 to obtain decoded data and/or control information. The receive processor 238 may provide the decoded data to a data sink 239 (which may be a data pipeline, a data queue, and/or another type of data sink) and provide the decoded control information to a processor, such as the controller/processor 240.

The network node 110 may use the scheduler 246 to schedule one or more UEs 120 for downlink or uplink communications. In some aspects, the scheduler 246 may use DCI to dynamically schedule DL transmissions to the UE 120 and/or UL transmissions from the UE 120. In some examples, the scheduler 246 may allocate recurring time domain resources and/or frequency domain resources that the UE 120 may use to transmit and/or receive communications using an RRC configuration (for example, a semi-static configuration) , for example, to perform semi-persistent scheduling (SPS) or to configure a configured grant (CG) for the UE 120.

One or more of the transmit processor 214, the TX MIMO processor 216, the modem 232, the antenna 234, the MIMO detector 236, the receive processor 238, and/or the controller/processor 240 may be included in an RF chain of the network node 110. An RF chain may include one or more filters, mixers, oscillators, amplifiers, analog-to-digital converters (ADCs) , and/or other devices that convert between an analog signal (such as for transmission or reception via an air interface) and a digital signal (such as for processing by one or more processors of the network node 110) . In some aspects, the RF chain may be or may be included in a transceiver of the network node 110.

In some examples, the network node 110 may use the communication unit 244 to communicate with a core network and/or with other network nodes. The communication unit 244 may support wired and/or wireless communication protocols and/or connections, such as Ethernet, optical fiber, common public radio interface (CPRI) , and/or a wired or wireless backhaul, among other examples. The network node 110 may use the communication unit 244 to transmit and/or receive data associated with the UE 120 or to perform network control signaling, among other examples. The communication unit 244 may include a transceiver and/or an interface, such as a network interface.

The UE 120 may include a set of antennas 252 (shown as antennas 252a through 252r, where r ≥ 1) , a set of modems 254 (shown as modems 254a through 254u, where u ≥ 1) , a MIMO detector 256, a receive processor 258, a data sink 260, a data source 262, a transmit processor 264, a TX MIMO processor 266, a controller/processor 280, a memory 282, and/or a communication manager 140, among other examples. One or more of the components of the UE 120 may be included in a housing 284. In some aspects, one or a combination of the antenna (s) 252, the modem (s) 254, the MIMO detector 256, the receive processor 258, the transmit processor 264, or the TX MIMO processor 266 may be included in a transceiver that is included in the UE 120. The transceiver may be under control of and used by one or more processors, such as the controller/processor 280, and in some aspects in conjunction with processor-readable code stored in the memory 282, to perform aspects of the methods, processes, or operations described herein. In some aspects, the UE 120 may include another interface, another communication component, and/or another component that facilitates communication with the network node 110 and/or another UE 120.

For downlink communication from the network node 110 to the UE 120, the set of antennas 252 may receive the downlink communications or signals from the network node 110 and may provide a set of received downlink signals (for example, R received signals) to the set of modems 254. For example, each received signal may be provided to a respective demodulator component (shown as DEMOD) of a modem 254. Each modem 254 may use the respective demodulator component to condition (for example, filter, amplify, downconvert, and/or digitize) a received signal to obtain input samples. Each modem 254 may use the respective demodulator component to further demodulate or process the input samples (for example, for OFDM) to obtain received symbols. The MIMO detector 256 may obtain received symbols from the set of modems 254, may perform MIMO detection on the received symbols if applicable, and may provide detected symbols. The receive processor 258 may process (for example, decode) the detected symbols, may provide decoded data for the UE 120 to the data sink 260 (which may include a data pipeline, a data queue, and/or an application executed on the UE 120) , and may provide decoded control information and system information to the controller/processor 280.

For uplink communication from the UE 120 to the network node 110, the transmit processor 264 may receive and process data ( “uplink data” ) from a data source 262 (such as a data pipeline, a data queue, and/or an application executed on the UE 120) and control information from the controller/processor 280. The control information may include one or more parameters, feedback, one or more signal measurements, and/or other types of control information. In some aspects, the receive processor 258 and/or the controller/processor 280 may determine, for a received signal (such as received from the network node 110 or another UE) , one or more parameters relating to transmission of the uplink communication. The one or more parameters may include an RSRP parameter, a received signal strength indicator (RSSI) parameter, an RSRQ parameter, a CQI parameter, or a transmit power control (TPC) parameter, among other examples. The control information may include an indication of the RSRP parameter, the RSSI parameter, the RSRQ parameter, the CQI parameter, the TPC parameter, and/or another parameter. The control information may facilitate parameter selection and/or scheduling for the UE 120 by the network node 110.

The transmit processor 264 may generate reference symbols for one or more reference signals, such as an uplink demodulation reference signal (DMRS) , an uplink sounding reference signal (SRS) , and/or another type of reference signal. The symbols from the transmit processor 264 may be precoded by the TX MIMO processor 266, if applicable, and further processed by the set of modems 254 (for example, for DFT-s-OFDM or CP-OFDM) . The TX MIMO processor 266 may perform spatial processing (for example, precoding) on the data symbols, the control symbols, the overhead symbols, and/or the reference symbols, if applicable, and may provide a set of output symbol streams (for example, U output symbol streams) to the set of modems 254. For example, each output symbol stream may be provided to a respective modulator component (shown as MOD) of a modem 254. Each modem 254 may use the respective modulator component to process (for example, to modulate) a respective output symbol stream (for example, for OFDM) to obtain an output sample stream. Each modem 254 may further use the respective modulator component to process (for example, convert to analog, amplify, filter, and/or upconvert) the output sample stream to obtain an uplink signal.

The modems 254a through 254u may transmit a set of uplink signals (for example, R uplink signals or U uplink symbols) via the corresponding set of antennas 252. An uplink signal may include a UCI communication, a MAC-CE communication, an RRC communication, or another type of uplink communication. Uplink signals may be transmitted on a PUSCH, a PUCCH, and/or another type of uplink channel. An uplink signal may carry one or more TBs of data. Sidelink data and control transmissions (that is, transmissions directly between two or more UEs 120) may generally use similar techniques as were described for uplink data and control transmission, and may use sidelink-specific channels such as a physical sidelink shared channel (PSSCH) , a physical sidelink control channel (PSCCH) , and/or a physical sidelink feedback channel (PSFCH) .

One or more antennas of the set of antennas 252 or the set of antennas 234 may include, or may be included within, one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays, among other examples. An antenna panel, an antenna group, a set of antenna elements, or an antenna array may include one or more antenna elements (within a single housing or multiple housings) , a set of coplanar antenna elements, a set of non-coplanar antenna elements, or one or more antenna elements coupled with one or more transmission or reception components, such as one or more components of Fig. 2. As used herein, “antenna” can refer to one or more antennas, one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays. “Antenna panel” can refer to a group of antennas (such as antenna elements) arranged in an array or panel, which may facilitate beamforming by manipulating parameters of the group of antennas. “Antenna module” may refer to circuitry including one or more antennas, which may also include one or more other components (such as filters, amplifiers, or processors) associated with integrating the antenna module into a wireless communication device.

In some examples, each of the antenna elements of an antenna 234 or an antenna 252 may include one or more sub-elements for radiating or receiving radio frequency signals. For example, a single antenna element may include a first sub-element cross-polarized with a second sub-element that can be used to independently transmit cross-polarized signals. The antenna elements may include patch antennas, dipole antennas, and/or other types of antennas arranged in a linear pattern, a two-dimensional pattern, or another pattern. A spacing between antenna elements may be such that signals with a desired wavelength transmitted separately by the antenna elements may interact or interfere constructively and destructively along various directions (such as to form a desired beam) . For example, given an expected range of wavelengths or frequencies, the spacing may provide a quarter wavelength, a half wavelength, or another fraction of a wavelength of spacing between neighboring antenna elements to allow for the desired constructive and destructive interference patterns of signals transmitted by the separate antenna elements within that expected range.

The amplitudes and/or phases of signals transmitted via antenna elements and/or sub-elements may be modulated and shifted relative to each other (such as by manipulating phase shift, phase offset, and/or amplitude) to generate one or more beams, which is referred to as beamforming. The term “beam” may refer to a directional transmission of a wireless signal toward a receiving device or otherwise in a desired direction. “Beam” may also generally refer to a direction associated with such a directional signal transmission, a set of directional resources associated with the signal transmission (for example, an angle of arrival, a horizontal direction, and/or a vertical direction) , and/or a set of parameters that indicate one or more aspects of a directional signal, a direction associated with the signal, and/or a set of directional resources associated with the signal. In some implementations, antenna elements may be individually selected or deselected for directional transmission of a signal (or signals) by controlling amplitudes of one or more corresponding amplifiers and/or phases of the signal (s) to form one or more beams. The shape of a beam (such as the amplitude, width, and/or presence of side lobes) and/or the direction of a beam (such as an angle of the beam relative to a surface of an antenna array) can be dynamically controlled by modifying the phase shifts, phase offsets, and/or amplitudes of the multiple signals relative to each other.

Different UEs 120 or network nodes 110 may include different numbers of antenna elements. For example, a UE 120 may include a single antenna element, two antenna elements, four antenna elements, eight antenna elements, or a different number of antenna elements. As another example, a network node 110 may include eight antenna elements, 24 antenna elements, 64 antenna elements, 128 antenna elements, or a different number of antenna elements. Generally, a larger number of antenna elements may provide increased control over parameters for beam generation relative to a smaller number of antenna elements, whereas a smaller number of antenna elements may be less complex to implement and may use less power than a larger number of antenna elements. Multiple antenna elements may support multiple-layer transmission, in which a first layer of a communication (which may include a first data stream) and a second layer of a communication (which may include a second data stream) are transmitted using the same time and frequency resources with spatial multiplexing.

The network node 110, the controller/processor 240 of the network node 110, the UE 120, the controller/processor 280 of the UE 120, the CU 310, the DU 330, the RU 340, or any other component (s) of Figs. 1, 2, or 3 may implement one or more techniques or perform one or more operations associated with configuration of entropy coding for channel state feedback, as described in more detail elsewhere herein. For example, the controller/processor 240 of the network node 110, the controller/processor 280 of the UE 120, any other component (s) of Fig. 2, the CU 310, the DU 330, or the RU 340 may perform or direct operations of, for example, process 700 of Fig. 7, process 800 of Fig. 8, process 900 of Fig. 9, process 1000 of Fig. 10, process 1100 of Fig. 11, process 1200 of Fig. 12, or other processes as described herein (alone or in conjunction with one or more other processors) . The memory 242 may store data and program codes for the network node 110, the network node 110, the CU 310, the DU 330, or the RU 340. The memory 282 may store data and program codes for the UE 120. In some examples, the memory 242 or the memory 282 may include a non-transitory computer-readable medium storing a set of instructions (for example, code or program code) for wireless communication. The memory 242 may include one or more memories, such as a single memory or multiple different memories (of the same type or of different types) . The memory 282 may include one or more memories, such as a single memory or multiple different memories (of the same type or of different types) . For example, the set of instructions, when executed (for example, directly, or after compiling, converting, or interpreting) by one or more processors of the network node 110, the UE 120, the CU 310, the DU 330, or the RU 340, may cause the one or more processors to perform process 700 of Fig. 7, process 800 of Fig. 8, process 900 of Fig. 9, process 1000 of Fig. 10, process 1100 of Fig. 11, process 1200 of Fig. 12, or other processes as described herein. In some examples, executing instructions may include running the instructions, converting the instructions, compiling the instructions, and/or interpreting the instructions, among other examples.

In some aspects, the UE 120 includes means for receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF; and/or means for transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. In some aspects, the UE 120 includes means for receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and/or means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters. In some aspects, the UE 120 includes means for receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and/or means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters. The means for the UE 120 to perform operations described herein may include, for example, one or more of communication manager 140, antenna 252, modem 254, MIMO detector 256, receive processor 258, transmit processor 264, TX MIMO processor 266, controller/processor 280, or memory 282.

In some aspects, the network node 110 includes means for transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF; and/or means for receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. In some aspects, the network node 110 includes means for transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and/or means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters. In some aspects, the network node 110 includes means for transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and/or means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters. The means for the network node to perform operations described herein may include, for example, one or more of communication manager 150, transmit processor 220, TX MIMO processor 230, modem 232, antenna 234, MIMO detector 236, receive processor 238, controller/processor 240, memory 242, or scheduler 246.

In some aspects, an individual processor may perform all of the functions described as being performed by the one or more processors. In some aspects, one or more processors may collectively perform a set of functions. For example, a first set of (one or more) processors of the one or more processors may perform a first function described as being performed by the one or more processors, and a second set of (one or more) processors of the one or more processors may perform a second function described as being performed by the one or more processors. The first set of processors and the second set of processors may be the same set of processors or may be different sets of processors. Reference to “one or more processors” should be understood to refer to any one or more of the processors described in connection with Fig. 2. Reference to “one or more memories” should be understood to refer to any one or more memories of a corresponding device, such as the memory described in connection with Fig. 2. For example, functions described as being performed by one or more memories can be performed by the same subset of the one or more memories or different subsets of the one or more memories.

While blocks in Fig. 2 are illustrated as distinct components, the functions described above with respect to the blocks may be implemented in a single hardware, software, or combination component or in various combinations of components. For example, the functions described with respect to the transmit processor 264, the receive processor 258, and/or the TX MIMO processor 266 may be performed by or under the control of the controller/processor 280.

Deployment of communication systems may be arranged in multiple manners with various components or constituent parts. In some examples, a network, a network node, a network entity, a mobility element of a network, a radio access network (RAN) node, a core network node, a network element, a base station, or a network equipment may be implemented in an aggregated or disaggregated architecture. For example, a base station (such as a Node B (NB) , an evolved NB (eNB) , an NR base station, a 5G NB, an access point (AP) , a TRP, or a cell, among other examples) , or one or more units (or one or more components) performing base station functionality, may be implemented as an aggregated base station (also known as a standalone base station or a monolithic base station) or a disaggregated base station. “Network entity” or “network node” may refer to a disaggregated base station, or to one or more units of a disaggregated base station (such as one or more CUs, one or more DUs, one or more RUs, or a combination thereof) .

An aggregated base station (e.g., an aggregated network node) may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node (e.g., within a single device or unit) . A disaggregated base station (e.g., a disaggregated network node) may be configured to utilize a protocol stack that is physically or logically distributed among two or more units (such as one or more CUs, one or more DUs, or one or more RUs) . In some examples, a CU may be implemented within a network node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed throughout one or multiple other network nodes. The DUs may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU also can be implemented as virtual units, such as a virtual central unit (VCU) , a virtual distributed unit (VDU) , or a virtual radio unit (VRU) , among other examples.

Base station-type operation or network design may consider aggregation characteristics of base station functionality. For example, disaggregated base stations may be utilized in an integrated access and backhauling (IAB) network, an open radio access network (O-RAN (such as the network configuration sponsored by the O-RAN Alliance) ) , or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN) ) to facilitate scaling of communication systems by separating base station functionality into one or more units that can be individually deployed. A disaggregated base station may include functionality implemented across two or more units at various physical locations, as well as functionality implemented for at least one unit virtually, which can enable flexibility in network design. The various units of the disaggregated base station can be configured for wired or wireless communication with at least one other unit of the disaggregated base station.

Fig. 3 is a diagram illustrating an example disaggregated base station architecture 300 in accordance with the present disclosure. One or more components of the example disaggregated base station architecture 300 may be, may include, or may be included in one or more network nodes (such one or more network nodes 110) . The disaggregated base station architecture 300 may include a CU 310 that can communicate directly with a core network 320 via a backhaul link, or that can communicate indirectly with the core network 320 via one or more disaggregated control units, such as a Non-RT RIC 350 associated with a Service Management and Orchestration (SMO) Framework 360 and/or a Near-RT RIC 370 (for example, via an E2 link) . The CU 310 may communicate with one or more DUs 330 via respective midhaul links, such as via F1 interfaces. Each of the DUs 330 may communicate with one or more RUs 340 via respective fronthaul links. Each of the RUs 340 may communicate with one or more UEs 120 via respective RF access links. In some deployments, a UE 120 may be simultaneously served by multiple RUs 340.

Each of the components of the disaggregated base station architecture 300, including the CUs 310, the DUs 330, the RUs 340, the Near-RT RICs 370, the Non-RT RICs 350, and the SMO Framework 360, may include one or more interfaces or may be coupled with one or more interfaces for receiving or transmitting signals, such as data or information, via a wired or wireless transmission medium.

In some aspects, the CU 310 may be logically split into one or more CU-UP units and one or more CU-CP units. A CU-UP unit may communicate bidirectionally with a CU-CP unit via an interface, such as the E1 interface when implemented in an O-RAN configuration. The CU 310 may be deployed to communicate with one or more DUs 330, as necessary, for network control and signaling. Each DU 330 may correspond to a logical unit that includes one or more base station functions to control the operation of one or more RUs 340. For example, a DU 330 may host various layers, such as an RLC layer, a MAC layer, or one or more PHY layers, such as one or more high PHY layers or one or more low PHY layers. Each layer (which also may be referred to as a module) may be implemented with an interface for communicating signals with other layers (and modules) hosted by the DU 330, or for communicating signals with the control functions hosted by the CU 310. Each RU 340 may implement lower layer functionality. In some aspects, real-time and non-real-time aspects of control and user plane communication with the RU (s) 340 may be controlled by the corresponding DU 330.

The SMO Framework 360 may support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO Framework 360 may support the deployment of dedicated physical resources for RAN coverage requirements, which may be managed via an operations and maintenance interface, such as an O1 interface. For virtualized network elements, the SMO Framework 360 may interact with a cloud computing platform (such as an open cloud (O-Cloud) platform 390) to perform network element life cycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface, such as an O2 interface. A virtualized network element may include, but is not limited to, a CU 310, a DU 330, an RU 340, a non-RT RIC 350, and/or a Near-RT RIC 370. In some aspects, the SMO Framework 360 may communicate with a hardware aspect of a 4G RAN, a 5G NR RAN, and/or a 6G RAN, such as an open eNB (O-eNB) 380, via an O1 interface. Additionally or alternatively, the SMO Framework 360 may communicate directly with each of one or more RUs 340 via a respective O1 interface. In some deployments, this configuration can enable each DU 330 and the CU 310 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

The Non-RT RIC 350 may include or may implement a logical function that enables non-real-time control and optimization of RAN elements and resources, AI/ML workflows including model training and updates, and/or policy-based guidance of applications and/or features in the Near-RT RIC 370. The Non-RT RIC 350 may be coupled to or may communicate with (such as via an A1 interface) the Near-RT RIC 370. The Near-RT RIC 370 may include or may implement a logical function that enables near-real-time control and optimization of RAN elements and resources via data collection and actions via an interface (such as via an E2 interface) connecting one or more CUs 310, one or more DUs 330, and/or an O-eNB with the Near-RT RIC 370.

In some aspects, to generate AI/ML models to be deployed in the Near-RT RIC 370, the Non-RT RIC 350 may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC 370 and may be received at the SMO Framework 360 or the Non-RT RIC 350 from non-network data sources or from network functions. In some examples, the Non-RT RIC 350 or the Near-RT RIC 370 may tune RAN behavior or performance. For example, the Non-RT RIC 350 may monitor long-term trends and patterns for performance and may employ AI/ML models to perform corrective actions via the SMO Framework 360 (such as reconfiguration via an O1 interface) or via creation of RAN management policies (such as A1 interface policies) .

As indicated above, Fig. 3 is provided as an example. Other examples may differ from what is described with regard to Fig. 3.

A CSI report configuration can include a codebook, which is used as a PMI from which a UE can select a set of best PMI codewords that the UE indicates as a bit sequence transmitted to a network node. In some examples, a UE may use an AI or machine learning (ML) technique to encode CSI feedback and a network node may use a corresponding AI/ML technique to decode the encoded AI-based CSI feedback. The UE may use a downlink channel matrix, a set of downlink precoders, or an interference covariance matrix as an input to an AI model and the network node may identify the downlink channel matrix, a transmit covariance matrix, the set of downlink precoders, the interference covariance matrix R_nn, a raw downlink channel, or a whitened downlink channel as outputs from processing received CSI feedback using a corresponding AI model.

Some UEs may be configured with a plurality of different AI/ML models for a plurality of different scenarios. For example, a UE may be configurable with an AI/ML model for an indoor or outdoor scenario, a line of sight or non-light of sight scenario, a geographical location, a serving cell, a channel statistic (e.g., a particular delay spread or signal to noise ratio) , or a particular type of the UE. The different AI/ML models may be trained with different datasets or data samples, which may provide more accurate performance when a UE uses, in a particular scenario, an AI/ML model trained for the particular scenario (e.g., using data collected from the same or similar scenarios) . In other words, for example, a UE that is operating outdoors and using an encoder AI/ML model trained on datasets of CSI feedback from outdoor observations may provide CSF that can be more accurately recovered by a network node with a corresponding decoder AI/ML model than if the UE was operating outdoors using an encoder AI/ML model trained on datasets of CSI feedback from indoor observations.

In a CSI compression using two-sided model use case, as described above with respect to the encoder and decoder, various parameters may be specified. For example, a vector quantization scheme, a format of a vector quantization codebook, or a size of the vector quantization codebook may be configured. Similarly, a size of segments and a segmentation algorithm for CSI generation model output may be configured. In another example, a UE may use a scalar quantization scheme, in which case, a configurable parameter may include whether to perform uniform quantization or non-uniform quantization. Additionally, a format of quantization, such as a quantization granularity or a distribution of bits assigned to each float, may be specified for a scalar quantization scheme.

Figs. 4A and 4B are diagrams illustrating an example 400 of data compression for channel state feedback, in accordance with the present disclosure. As shown in Figs. 4A and 4B, a quantization and de-quantization process may enable data compression of the channel state feedback.

When a UE 120 uses an AI/ML model for data compression of CSF data, the UE 120 may perform a set of procedures to compress data. One procedure that the UE 120 can perform is vector quantization (VQ) . In VQ, the UE 120 quantizes each input vector and maps each quantized, input vector to a vector of a codebook (e.g., with a configured vector size) . In other words, the UE 120 may receive an input V_in, as shown by reference number 401. Further, the UE 120 may divide the input into a set of input vectors Z_e, as shown by reference number 405. The UE 120 may divide Z_e into a set of sub-vectors of size d, such as a size of 2 units or a size of 4 units. An example of a sub-vector is shown by reference number 415, which indicates a sub-vector of size 2 units, [Z_e0, Z_e1] . The UE 120 may select a codeword from a vector of a quantization codebook Z_embd, as shown by reference number 420, and map the sub-vectors to the vector of the quantization codebook ( [Z_q0, Z_q1] ) . In some examples, the UE 120 may select a quantization codebook (CB) from a group of K codebooks. Fig. 4B, shows an example of a quantization codebook, in which vector values from -5 to 5 for a size of 2 units can be quantized into a discrete group of 16 values. Returning to Fig. 4A, the UE 120 may combine the mapped sub-vectors to generate an output, quantized vector, as shown by reference number 425. The UE 120 may transmit information identifying the quantized vector to the network node 110, which may perform decoding on the quantized vector. For example, the network node 110 may perform a de-quantization procedure to resolve a set of sub-vectors [Z_q0, Z_q1] , as shown by reference number 425. The network node 110 may combine the set of sub-vectors to obtain a quantization vector Z_q, as shown by reference number 430. The network node 110 may combine a plurality of quantization vectors to obtain an output V_out, which may be a recovery of the input V_in and which corresponds to a value from which the network node 110 can estimate a channel and select a configuration for the channel.

As indicated above, Figs. 4A and 4B are provided as examples. Other examples may differ from what is described with respect to Figs. 4A and 4B.

Figs. 5A and 5B are diagrams illustrating an example 500 of data compression using vector quantization and entropy coding, in accordance with the present disclosure. As shown in Fig. 5A, example 500 includes a UE 120 and a network node 110 (shown as “NN 110” ) .

As further shown in Fig. 5A, and by reference number 510, the UE 120 may input data to an encoder (afirst encoder for generating CSI data from one or more measurements) , which may be an AI/ML model in some examples. For example, the UE 120 may input a set of channel metrics to the encoder, such as a downlink channel matrix (H) , a transmit covariance matrix, a downlink precoder (V) , an interference covariance matrix (R_nn) , a raw downlink channel, or a whitened downlink channel. In some examples, the downlink precoder or another parameter is generated by the UE 120 using a singular value decomposition (SVD) technique applied to the downlink channel matrix. In this example, the UE 120 may use the encoder to generate a latent message that is to be decoded at the network node 110 (to recover H, V, or R_nn, among other examples, or to determine a singular value diagonal matrix (S) , a right singular vector matrix (V) or a combination of the two, SV, among other examples) .

As further shown in Fig. 5A, and by reference number 520, the UE 120 may use a quantizer component to perform vector quantization (VQ) on an output of the encoder, such as a latent vector Z. For example, the UE 120 may use a VQ codebook 521 to quantize the output of the encoder and generate an embedding vector Z_embd, as described above. The UE 120 may use a entropy coding (EC) probability density function or probability mass function (PMF) 522 that is defined over an alphabet used in entries of an embedding vector. In other words, for VQ, the UE 120 may have an alphabet of {0, 1, …, K-1} where K is a codebook size for VQ. In this example, rather than transmitting the embedding vector (or one or more bits representing the embedding vector) , which is a compressed value relative to the latent message, the UE 120 may perform a further data compression procedure, as described herein.

As further shown in Fig. 5A, and by reference number 530, the UE 120 may use an EC encoder to encode the embedding vector as a data-compressed embedding vector. For example, the UE 120 may generate a CSF message using the embedding vector Z_embd and an entropy coding PMF 522. In some examples, the UE 120 may perform a Huffman coding procedure to generate the CSF message. In some examples, the UE 120 may perform an arithmetic coding procedure to generate the CSF message.

As shown in Fig. 5B, and by reference number 535a, in the Huffman coding procedure, the UE 120 may generate a look-up table 536 (or another type of data structure) . The look-up table includes a mapping of symbols [S0, S1, S2, S3, …] to bit sequences [00, 01, 10, 111, …] . The symbols in the look-up table are symbols that represent the embedding vector, which is to be entropy coded, and are ordered in order of frequency of use. The symbols map to bit sequences of increasing length, such that more frequently used symbols are mapped to smaller bit sequences. For example, when a first given symbol k is repeated 5 instances for the embedding vector and a second given symbol l is repeated 2 instances for the embedding vector, the first symbol k may be represented as S0 and map to bit sequence ‘00’ , and the second symbol l may be represented as S3 and map to bit sequence ‘111’ . In this example, the bit sequence ‘00’ is repeated 5 times when transmitted, and the bit sequence ‘111’ is repeated 1 time. In some examples, the bit sequences are selected such that no bit sequence starts with another bit sequence. For example, in the bit sequence in Fig. 5B, binary values ‘11’ , ‘100’ , ‘101’ , and ‘110’ are skipped in the lookup table as each starts with a bit sequence already included in the look-up table. In this example, omitting bit sequences that start with other bit sequences enables a decoder to decode the bit sequences without using an indicator of where each bit sequence ends. When performing Huffman coding, the UE 120 selects input symbols S_i and uses the look-up table (or another type of algorithm) to transform or map the input symbols to output codewords C_i, which are the bit sequences.

As further shown in Fig. 5B, and by reference number 535b, in the arithmetic coding procedure, the UE 120 may use an arithmetic coding algorithm (shown as “AC alg” ) to transform a set of input symbols to an output bit sequence. The arithmetic coding algorithm may be selected from a plurality of possible arithmetic coding algorithms that can be used. In some examples, the arithmetic coding algorithm using the entropy coding probability mass function (EC PMF) 522 as an input for generating an output sequence. In arithmetic coding, the UE 120 encodes an entire message (aplurality of symbols) into a single number, such as an arbitrary-precision fraction q in a range of 0.0 ≤ q ≤ 1.0. To perform arithmetic coding, the UE 120 divides the interval [0, 1] into a plurality of values that map to a plurality of symbols in association with a probability of each symbol occurring. Accordingly, symbols with a higher probability of occurring occupy a larger relative portion of the interval. In some examples, the UE 120 may recursively assign values or sub-intervals to symbols as new symbols are being encoded. When performing the arithmetic coding procedure, the UE 120 selects input symbols S_i and uses the arithmetic coding algorithm and the EC PMF to generate an output sequence C including a set of output codewords.

Returning to Fig. 5A, and as shown by reference number 540, the network node 110 may receive a CSF message from the UE 120, conveying entropy-coded, vector-quantized data of a CSI report, and may perform EC decoding using a decoder, such as an entropy coding decoder. The network node 110 may use the EC PMF 522 as input to the decoder to decode the Huffman coding or arithmetic coding applied to the CSF message. For example, with arithmetic coding (and the corresponding decoding) , the network node 110 may use the decoder to perform an inverse operation in which a fraction of a value x within an interval [0, 1] is traversed digit-by-digit after a decimal point of x to determine a mapping to a first symbol, a second symbol, a third symbol, and so on. Similarly, with Huffman coding, the network node 110 may use the decoder to demap binary values to symbols according to a look-up table (or another type of data structure or algorithm for configuring a mapping) . Based at least in part on performing EC decoding, the network node 110 recovers the embedding vector Z_embd.

As further shown in Fig. 5A, and by reference number 550, the network node 110 may perform a de-quantization procedure on the embedding vector to recover a vector representing data of the CSI report. For example, the network node 110 may de-map a set of quantized values of Z_embd, using the vector quantization codebook 521, to recover the vector Z_e. As shown by reference number 560, the network node 110 may decode the vector Z_e to identify one or more output parameters, from which the network node 110 can derive a channel estimate and configure subsequent communication on a channel. For example, the network node 110 may recover the values of H, V, SV, or R_nn that were encoded at the UE 120. Using the recovered values, the network node 110 may select a precoding matrix, a modulation and coding scheme (MCS) , a transmit power, a resource allocation, a quasi-co-location (QCL) parameter, or another communication configuration for subsequent communication with the UE 120 on a channel.

As indicated above, Figs. 5A and 5B are provided as examples. Other examples may differ from what is described with respect to Figs. 5A and 5B.

A network node may transmit a CSI-RS to a UE, which may perform a measurement of the CSI-RS. The UE may estimate a downlink channel response using the measurement of the CSI-RS and may report a set of CSI indicators to the network node. By estimating a downlink channel at the UE, reporting the estimate of the downlink channel to the network node, and configuring transmissions on the downlink channel at the network node, the UE and the network node can achieve efficient communication.

The UE and the network node may use data compression and decompression techniques to reduce an amount of overhead associated with transmitting a CSF message conveying reporting CSI feedback data. The UE may perform a VQ procedure in which values of the CSI feedback data are divided into vectors and the vectors are aligned to a set of code words of a quantization codebook. Further, the UE may perform an entropy coding technique to compress the sequences of bits. The UE may transmit, as the CSF message, an output sequence that represents a data compression of the CSI feedback data. The network node can recover the CSI feedback data by decoding the CSF message. For example, the network node may perform EC decoding and vector de-quantization to reverse the data compression techniques.

When the network node performs the above-mentioned procedures for decoding and recovering the CSF message, the network node may use one or more parameters or configurations to successfully obtain CSF message data, such as the CSI feedback data underlying the CSF message, from an encoded, compressed CSF message. For example, the network node may use information indicating which version of entropy coding has been used to determine whether to use a lookup table, as in Huffman coding, or an arithmetic algorithm, as in Arithmetic coding to convert a set of bits to a set of symbols, from which the CSF message can be recovered. As another example, to reverse an entropy coding procedure, the network node may use an estimate of a PMF that the UE used to derive a code word tree, as in Huffman coding, or as a parameter of the arithmetic algorithm, as in Arithmetic coding. When an encoder of the UE is not synchronized with a decoder of the network node. the network node may be unsuccessful or inaccurate at recovering the CSF message data. Accordingly, when the network node attempts to configure downlink transmissions using the CSF message data, which has been recovered unsuccessfully or inaccurately, the network node may select parameters for the downlink transmissions that result in a less efficient usage of channel resources and/or that result communication interruptions.

Various aspects relate generally to configuring entropy coding for CSF messages. Some aspects more specifically relate to a network node conveying, to a UE, information identifying a configuration of a CSF report, such as an AI-based CSF report. For example, the network node may transmit RRC signaling identifying a type of entropy coding that the UE is to perform or a PMF parameter for an entropy coding procedure. In some aspects, the network node may transmit RRC signaling indicating whether the UE is to apply entropy coding as multiple entropy coding procedures for multiple layers of VQ output, which may be the CSF message data, or whether the UE is to merge the multiple layers of VQ output and perform a single entropy coding procedure for the merged VQ output. In some aspects, the network node may indicate whether the UE is to transmit an indication of one or more parameters used for entropy coding along with transmitting an entropy coded message. For example, the network node may instruct the UE to transmit an indication of a length of an entropy coding output, which the network node can use for decoding.

In some aspects, the network node may transmit an indication of whether to activate or deactivate entropy coding. For example, the UE have the capability to adaptively use entropy coding or switching to using another technique and the network node may transmit an indication of which technique to use at which time. In some aspects, the network node may transmit an indication of a maximum payload size for a CSI report. For example, the network node may configure the UE such that when the UE determines that the maximum payload size is exceeded, the UE may be configured to switch from using entropy coding to not using entropy coding. In some aspects, the network node may transmit an indication of a payload structure for a CSF message encoded using entropy coding. For example, the network node may indicate that the UE is to transmit a first type of message with a first format or a second type of message with a second format. In this example, the first format may have a first set of fields for the UE to convey a configuration used for EC coding, and the second format may have a second set of fields for the UE to convey the configuration used for EC coding. Examples of the types of fields may include a field for identifying a length of an entropy coding output or whether entropy coding has been bypassed.

Figs. 6A-6F are diagrams illustrating an example 600 associated with configuration of entropy coding for channel state feedback, in accordance with the present disclosure. As shown in Fig. 6A, example 600 includes communication between a network node 110 and a UE 120.

As further shown in Fig. 6A, and by reference number 605, in some aspects, the UE 120 may transmit UE capability information to the network node 110. For example, the UE 120 may transmit an uplink message to the network node 110 to identify a UE capability relating to entropy coding. In this example, the UE capability information may indicate whether the UE 120 is capable of performing entropy coding. Additionally, or alternatively, the UE capability information may include an indication of one or more proposed or possible parameters that are to be used for an entropy coding configuration. In this example, the network node 110 may transmit, signaling, indicate, provide, or convey, among other examples a response message configuring the one or more proposed or possible parameters or rejecting the one or more proposed or possible parameters.

As further shown in Fig. 6A, and by reference number 610, the UE 120 may receive entropy coding configuration information from the network node 110. For example, the UE 120 may receive RRC signaling with one or more fields conveying the entropy coding configuration information. In this example, the RRC signaling may include one or more fields associated with signaling or indicating the entropy coding configuration information. In some aspects, the RRC signaling may include an RRC configuration of an AI/ML-based CSI report. For example, the UE 120 may receive RRC signaling including a first one or more parameters for configuring AI/ML-based CSI reporting and a second one or more parameters for configuring entropy coding.

In some aspects, the entropy coding configuration information is conveyed, indicated, or signaled, among other examples via a message. For example, the message may include one or more fields with one or more values that the UE 120 can interpret as one or more parameters of entropy coding configuration information. In this example, an RRC message may have an information element with a field set to a bit value of ‘0’ or ‘1’ with the UE interpreting a value of “0” as indicating a first configuration and “1” as indicating a second configuration. Similarly, the RRC message may have another information element with another field set to bit values of ‘00, ’ ‘01, ’ ‘10, ’ or ‘11’ to indicate which of 4 different possible configurations the UE 120 is to use. Although specific bit indications or field values are disclosed, it is contemplated that other bit indications or field values may be used.

Additionally, or alternatively, the UE 120 may receive the entropy coding configuration via another type of signaling. For example, the UE 120 may information identifying the entropy coding configuration in a model identification message. In this example, when the UE 120 receives a signaling message associated with selecting or configuring an AI/ML model for generating CSI feedback, the signaling message may include one or more fields to identify the entropy coding configuration. Additionally, or alternatively, the UE 120 may receive the entropy coding configuration via a model meta-information message. For example, when the UE 120 receives a signaling message associated with conveying model metadata for an AI/ML mode for generating CSI feedback, the signaling message may include one or more fields to identify the entropy coding configuration. Additionally, or alternatively, the UE 120 may receive the entropy coding configuration via a UE capability signaling message. For example, when the UE 120 transmits a UE capability message identifying one or more proposed or possible entropy coding configuration parameter values, the UE 120 may receive, from the network node 110, a response message confirming the one or more proposed or possible entropy coding configuration parameter values. Additionally, or alternatively, the UE 120 may receive entropy coding configuration via a combination of a plurality of messages or message types. For example, the UE 120 may receive first signaling conveying a first one or more parameters of the entropy coding configuration and second signaling conveying a second one or more parameters of the entropy coding configuration.

In some aspects, as shown by reference number 610a, the UE 120 may receive information identifying an entropy coding setting, such as information identifying one or more parameters for a CSF message conveying, indicating, or signaling entropy-coded CSF. For example, the UE 120 may receive information associated with ensuring alignment between an entropy coding encoder of the UE 120 and an entropy coding decoder of the network node 110. In this example, the one or more parameters may include a parameter identifying an entropy coding algorithm that is to be used by the UE 120 for entropy coding. For example, the UE 120 may receive an indication to use Huffman coding or Arithmetic coding. Additionally, or alternatively, the UE 120 may receive information identifying a probability mass function (PMF) or a probability density function defined over an alphabet used in entries of an embedding vector, as described above. Additionally, or alternatively, the UE 120 may receive information indicating whether the UE 120 is to use the same PMF over all entries of an embedding vector or different PMFs for different subsets of entries of the embedding vector. As shown in Fig. 6B, and by reference number 650, a set of embeddings Z_embd, which includes sequences {z_embd [0] , z_embd [1] , …, z_embd [N-1] } can be encoded, using the sequence {P_{z_0} [k] , P_{z_1} [k] , …, P_{z_N-1} [k] } for encoding of an entry in the embedding sequences. In this example, the network node 110 configures the UE 120 to encode a value Z₀ using P_{z_0} [k] , where k is a value in a symbol alphabet {0, …, K-1} . Further to this example, the network node 110 configures the UE 120 to vector quantize the set of embeddings using 4-dimensional VQ with a 2 bits-per-dimension PMF (resulting in 8 bits total for VQ) of P_{z_i} [k] , for k ε {0, 1, …, 255} . In some aspects, the network node 110 may configure the UE 120 to derive a PMF based on a whole vector or to derive separate PMFs for each entry within the whole vector. For example, the network node 110 may configure the UE 120 to use a single P_z [k] for Z₀, Z₁, etc., or different P_z [k] values for different Z₀, Z₁, etc. values.

In some aspects, the UE 120 may receive information indicating whether entropy coding is enabled or disabled. For example, when the UE 120 is configured to allow for adaptive enabling and disabling of entropy coding, the UE 120 may receive signaling indicating that entropy coding is to be enabled and used. When the UE 120 transmits a CSF message, the UE 120 may use entropy coding for compression of data of the CSF message. Additionally, or alternatively, when the UE 120 receives signaling indicating that entropy coding is to be disabled and not used, the UE 120 may transmit a CSF message that does not use entropy coding for compression (but which may or may not use vector quantization for compression) . In some aspects, the UE 120 may receive information instructing the UE 120 to indicate whether entropy coding is enabled. In other words, when the UE 120 is configured to disable entropy coding, such as for greedy-bypass, as described in detail below, the UE 120 may receive entropy coding configuration information indicating that the UE 120 is to include an indicator of whether entropy coding was enabled or disabled when the CSF message was generated. Additionally, or alternatively, the UE 120 may be configured to enable or disable entropy coding dynamically for each layer, each CSI report, or each group of CSI reports. In this example, the UE 120 may include an indicator of whether entropy coding was enabled or disabled for any layers, CSI reports, or groups of CSI reports in a CSF message in accordance with a parameter value of the entropy coding configuration information.

In some aspects, the UE 120 may receive information identifying a parameter that is specific to an entropy encoding algorithm. For example, when the UE 120 is configured to use Huffman coding, such as by specification or by an entropy coding configuration parameter, the UE 120 may receive an indication of a mapping of symbols to binary strings for a look-up table (LUT) . Although some aspects are described herein in terms of a look-up table, it is contemplated that other types of data structures or algorithms may be used for establishing a mapping between symbols and binary strings.

Additionally, or alternatively, when the UE 120 is configured to use finite precision Arithmetic coding, the UE 120 may receive an indication of a bitwidth to use in calculation of a sequence, such as a 16-bit bitwidth, a 32-bit bitwidth, a 64-bit bitwidth, a 128-bit bitwidth, or another example of a bitwidth. In finite precision Arithmetic coding, a fractional value is represented with a configured finite precision corresponding to a configured bitwidth.

Additionally, or alternatively, when the UE 120 is configured to use Arithmetic coding, the UE 120 may receive an indication of which Arithmetic coding algorithm or finite-precision implementation of Arithmetic coding the UE 120 is to use for entropy coding. For example, the UE 120 may receive an indication of whether entropy coding is applied separately over a VQ output of each layer of CSI data or whether entropy coding is applied jointly across all layers of VQ output of each layer of the CSI data. The CSI data that the UE 120 generates using, for example, an AI/ML model may be in the form of a matrix of values representing a channel estimate, with each column of the matrix being termed a “layer” of the CSI data. As shown in Fig. 6C, and by example 655, one example of CSI data includes a set of three layers, L1, L2, and L3. In this example, each layer is provided separately to an entropy coding encoder (of the UE 120) , as shown by reference number 656. The encoder encodes each layer using a PMF to generate three separately encoded (compressed) layers L1', L2', and L3', as shown by reference number 657. In contrast, as shown in Fig. 6C, and by example 660, the three layers are concatenated (or otherwise combined) to generate a joint layer L_J, as shown by reference number 661. In this example, the joint layer L_J is encoded to generate a single encoded (compressed) output L_J', as shown by reference number 662.

Additionally, or alternatively, when the UE 120 is configured to use Arithmetic coding, the UE 120 may receive an indication of whether to include a termination sequence (or end-of-sequence symbol) or may receive an indication of a value for a termination sequence of an encoding sequence, such as an indication to append a bit value of ‘01’ to an end of an encoding sequence. In this example, the network node 110 uses the termination sequence to determine where an encoding sequence terminates. In other words, entropy coding generates binary sequences with varying lengths that are based at least in part on values of the input vector as described above. Accordingly, the UE 120 may receive an indication of whether a length of an entropy coding output is to be signaled in a CSI report. For example, the network node 110 may instruct the UE 120 (by indicating with a parameter value) to include an indication of the length of the entropy coding output as a parameter value of the CSF message.

In some aspects, when the network node 110 does not instruct the UE 120 to report, in for example, a CSI message part 1, the indication of the length of the entropy coding output, the network node 110 may instruct the UE 120 to include an end-of-sequence symbol, e. In this example, the UE 120 may append e to an input vector and encode e with the input vector, as shown in Fig. 6D and by example 665. In this example, the UE 120 inputs one or more layers L as shown by reference number 666 and appends e to the one or more layers L. The UE 120 encodes the one or more layers L with e appended to generate an output L', as shown by reference number 667. Examples of values for e may include ‘00’ ‘01’ , or 11’ among other examples. Based on the UE 120 including e, a decoder of the network node 110 can detect e and terminate a decoding procedure as a response to detecting e. In some aspects, e may be appended to each layer (for separate encoding) or to a joint layer (for joint encoding over a plurality of layers) .

Returning to Fig. 6A, as shown by reference number 610b, in some aspects the UE 120 may receive information identifying a payload size limit for a CSF message conveying entropy-coded CSF. The output of entropy coding has a variable length and is compressed, relative, to the input of the entropy coding for some possible lengths. As illustration, Fig. 6E and diagram 670 show an example of possible payload sizes x relative to a level of data compression represented as a cumulative distribution function (CDF) F (x) . As shown, entropy coding achieves a greater level of data compression, in one example, for lengths of x ≤ 192 than is achieved without entropy coding. However, at lengths of x > 192, entropy coding results in increase in no data compression occurring (and, in fact, an increase in data) .

Accordingly, the UE 120 may be configured with an entropy coding with greedy-bypass configuration. In the entropy coding with greedy-bypass configuration, the UE 120 is configured with a maximum payload size that is based on a maximum number of non-zero coefficients that may be used for entropy coding. When an entropy coding output length is less or equal to the maximum payload size, the UE 120 uses the entropy coding output, thereby achieving data compression. When the entropy coding output length is greater than the maximum payload size, the UE 120 forgoes entropy coding (such as by including the entropy coding input, which is the vector quantization output) , thereby ensuring that there is no increase in data as a result of entropy coding. In some aspects, when the UE 120 is configured for greedy-bypass, the UE 120 is configured to include an indicator of whether entropy coding is used for a CSF message. For example, the UE 120 may receive entropy coding configuration information indicating that, when the entropy coding output length is greater than the maximum payload size, the UE 120 is to use the entropy coding input for the CSF message and include an indicator that the CSF message uses the entropy coding input rather than the entropy coding output. In this example, the UE 120 may use a 1-bit indication for whether greedy-bypass was used for the entirety of the CSF message or a 1-bit per layer, per CSI report, or per CSI report group to indicate whether greedy-bypass was used for a layer, a CSI report, or a CSI report group, respectively. The network node 110 may use the 1-bit indication (or 1-bit per layer indication) to determine whether to skip entropy coding decoding and, for example, move directly to vector de-quantization.

As shown by reference number 610c, in some aspects, the UE 120 may receive information identifying a payload structure for a CSF message conveying entropy-coded CSF message. For example, the UE 120 may receive entropy coding configuration information that indicates one or more fields the UE 120 is to include in a CSF message or a section of a CSF message. In this example, the one or more fields may be associated with indicating one or more parameters that the network node 110 is to use for decoding the entropy-coded CSF message and/or performing channel configuration. In some aspects, the entropy coding configuration information may indicate that the UE 120 is to include a parameter in a CSI part 1 section of a CSF message or a CSI part 2 section of a CSF message. Additional details regarding CSI are described with regard to 3GPP Technical Specification (TS) 38.212, Release 18, Version 18.0.0, Section 6.3 and 3GPP TS 38.214, Release 18, Version 18.0.0, Section 5.2.3. The CSI part 1 section and CSI part 2 section of the CSF message may include respective portions of a single transmission, such as header data and payload data or first payload data and second payload data, or respective transmissions that collectively comprise a CSF message, such as a first transmission and a second transmission.

As an example as shown in Fig. 6F, and by example 675, the network node 110 may configure the UE 120 to include a plurality of fields in a CSI part 1 section of a CSF message. In this example, the plurality of fields may include an RI field, a CQI field, a length field to indicate a length of an entropy coding output, and a bypass field to indicate whether entropy coding was bypassed in connection with a greedy-bypass technique. Similarly, in example 680, the network node 110 may configure the UE 120 to include a plurality of fields in a CSI part 2 section of a CSF message. In this example, the plurality of fields may include the length field and the bypass field. Additionally, or alternatively, the UE may be configured to include other fields, such as whether there is joint or separate encoding over a plurality of layers. Additionally, or alternatively, the UE 120 may indicate a total payload size in the CSI part 1 section and a payload size for each layer in the CSI part 2 section. In this example, the UE 120 may indicate a total payload value set of {c0, c1, …, c_i} in the CSI part 1 section and may indicate which value correspond to which layer in the CSI part 2 section.

Returning to Fig. 6A, and as shown by reference number 615, in some aspects, the UE 120 may receive one or more CSI-RS transmissions from the network node 110. For example, the network node 110 may transmit, signal, indicate, provide, or convey one or more CSI-RS signals for the UE 120 to perform one or more measurements and/or channel estimations thereon. Additionally, or alternatively, although some aspects are described in terms of a CSI-RS, it is contemplated that aspects described herein may be used with other types of reference signals, such as other downlink reference signals, other uplink reference signals, or other sidelink reference signals.

As further shown in Fig. 6A, and by reference number 620, in some aspects, the UE 120 may perform a CSI-RS measurement of the one or more CSI-RS transmissions. For example, the UE 120 may measure one or more channel metrics using the CSI-RS. In this example, the one or more channel metrics may include a channel quality metric, such as an RSRQ parameter, or a channel power metric, such as an RSRP parameter, among other examples. In some aspects, the UE 120 may determine one or more indicators. For example, the UE 120 may determine an RI value, a CQI value, or another indicator of a channel based on one or more measurements of the channel.

As further shown in Fig. 6A, and by reference number 625, in some aspects, the UE 120 may encode the CSI-RS measurement. For example, the UE 120 may perform one or more encoding procedures to generate a CSF message for transmission. In this example, the UE 120 may use an AI/ML model, which uses one or more measurements of the one or more CSI-RS transmissions as input, to generate an output of, for example, a set of vectors representing a channel. The UE 120 may quantize the set of vectors using vector quantization and may convert symbols of the quantized vectors into data-compressed bit sequences using entropy coding, as described above.

In some aspects, the UE 120 may encode a measurement of a CSI-RS in accordance with the entropy coding configuration. For example, the UE 120 may use an entropy coding algorithm or PMF indicated in the entropy coding configuration. The UE 120 may encode the measurement of the CSI-RS in accordance with the entropy coding configuration by using one or more parameters or settings indicated or identified by or in the entropy coding configuration. For example, when the entropy coding configuration includes a bit indicator to use Huffman coding, the UE 120 may encode the measurement of the CSI-RS in accordance with the entropy coding configuration by using Huffman coding as the algorithm for entropy coding. Similarly, when the UE 120 receives entropy coding configuration information indicating that the UE 120 is to include one or more fields in a CSF message, the UE 120 may encode and transmit the measurement of the CSI-RS in accordance with the entropy coding configuration information by including the one or more fields in the CSF message that conveys or is connected with the entropy-coded CSI feedback data.

Additionally, or alternatively, the UE 120 may use the same or a different PMF across entries of an embedding vector in accordance with the entropy coding configuration. Additionally, or alternatively, the UE 120 may use a particular configuration of Huffman coding or Arithmetic coding, among other examples, in accordance with the entropy coding configuration. Additionally, or alternatively, the UE 120 may perform entropy coding on a per layer basis or jointly across a plurality of layers in accordance with the entropy coding configuration. In some aspects, the UE 120 may append an end-of-sequence symbol to a sequence when performing entropy coding in accordance with the entropy coding configuration.

In some aspects, the UE 120 may forgo entropy coding for some CSF messages or a portion of a CSF message. For example, the UE 120 may determine that a maximum payload size is exceeded by an entropy coding output and may use a non-entropy-coded group of symbols, which may or may not have been vector quantized, as the CSF message. In this example, the UE 120 may include an indication of whether the UE 120 is not including the entropy coding output in the CSF message, such as based on a greedy-bypass technique, as described herein.

As further shown in Fig. 6A, and by reference number 630, the UE 120 may transmit a CSF message to the network node 110. For example, the UE 120 may transmit one or more transmissions that include one or more fields to convey the CSF message, such as one or more fields to convey a group of bit sequences. Additionally, or alternatively, the UE 120 may transmit one or more transmissions that include one or more fields to convey control information. For example, the UE 120 may convey an indication of whether entropy coding was used, a length of an entropy coding output, a PMF used for entropy coding, or another parameter, such as another parameter described herein.

As further shown in Fig. 6A, and by reference number 635, in some aspects, the network node 110 may decode the CSF message. For example, the network node 110 may receive the CSF message and decode the message in accordance with the entropy coding configuration information. In this example, the network node 110 may use the entropy coding configuration information as one or more settings for the decoding. As an example, when the network node 110 receives control information with the CSF message identifying a PMF for encoding or a length of an entropy coding output, the network node 110 may configure a decoder thereof using the PMF or the length of the entropy coding output. Additionally, or alternatively, when the network node 110 indicates that the UE 120 is to use an entropy coding algorithm, such as Huffman coding, the network node 110 may decode the CSF message in accordance with the entropy coding configuration information by using Huffman coding for decoding. In this example, the network node 110 may use a lookup table associated with Huffman coding to perform mapping of bit sequences to symbols, thereby performing lossless decoding of data-compressed entropy-coded CSI feedback data. Additionally, or alternatively, the network node 110 may perform vector de-quantization. Additionally, or alternatively, the network node 110 may use an AI/ML model to recover channel measurements or a channel estimate from the vector de-quantized data. For example, the network node 110 may use one side of an AI/ML model, for which the other side of the AI/ML model (atwo-sided AI/ML model) is operating on the UE 120. In this example, the side of the AI/ML model operating on the network node 110 outputs a downlink channel matrix, a transmit covariance matrix, one or more downlink precoders, an interference covariance matrix, a raw channel, or a whitened channel, among other examples that was an input to the side of the AI/ML model operating on the UE 120.

As further shown in Fig. 6A, and by reference number 640, in some aspects, the network node 110 may perform a channel configuration procedure. For example, the network node 110 may configure one or more parameters for a subsequent communication on a channel. In this example, the network node 110 may configure a modulation and coding scheme (MCS) , a downlink precoder, a transmit power, a set of resources, or a quasi-co-location (QCL) parameter, among other examples using the decoded CSF message.

As indicated above, Figs. 6A-6F are provided as one or more examples. Other examples may differ from what is described with respect to Figs. 6A-6F.

Fig. 7 is a diagram illustrating an example process 700 performed, for example, at a UE or an apparatus of a UE, in accordance with the present disclosure. Example process 700 is an example where the apparatus or the UE (e.g., UE 120 or the apparatus 1300) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 7, in some aspects, process 700 may include receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF (block 710) . For example, the UE (e.g., using communication manager 140 and/or reception component 1302, depicted in Fig.

13) may receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF, as described above.

As further shown in Fig. 7, in some aspects, process 700 may include transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (block 720) . For example, the UE (e.g., using communication manager 140 and/or transmission component 1304, depicted in Fig. 13) may transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information, as described above.

Process 700 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, process 700 includes transmitting UE capability information indicating a capability for entropy coding, and wherein receiving the entropy coding configuration information comprises receiving the entropy coding configuration information as a response to transmitting the UE capability information.

In a second aspect, alone or in combination with the first aspect, process 700 includes receiving a CSI-RS, performing a measurement of the CSI-RS, and encoding, in accordance with the entropy coding configuration information and using an encoder, the measurement of the CSI-RS using entropy coding to generate at least a portion of the payload of the CSF message, and wherein transmitting the CSF message comprises transmitting the CSF message to convey the at least the portion of the payload of the CSF message.

In a third aspect, alone or in combination with one or more of the first and second aspects, the one or more fields include at least one of a field indicating a parameter relating to a length of an entropy coding output, a field indicating a parameter relating to an entropy coding bypass indication, or a combination thereof.

In a fourth aspect, alone or in combination with one or more of the first through third aspects, the one or more fields are included in a first part of the CSF message.

In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, the one or more fields include at least one of a field indicating a parameter relating to a maximum payload across a plurality of layers of a CSF report of the CSF message, a field indicating a parameter relating to an entropy coding output for each layer of the plurality of layers, a field indicating a parameter relating to a total payload across the plurality of layers of the CSF report of the CSF message, or a combination thereof.

In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, the one or more fields are included in at least one of a second part of the CSF message or an uplink control information element signaled in connection with the CSF message.

In a seventh aspect, alone or in combination with one or more of the first through sixth aspects, the entropy coding configuration information is signaled via at least one of a model identification message, a model meta-information message, a radio resource control configuration message, a UE capability signaling message, or a combination thereof.

In an eighth aspect, alone or in combination with one or more of the first through seventh aspects, the entropy coding configuration information includes one or more parameters, the one or more parameters including a parameter identifying at least one of an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

In a ninth aspect, alone or in combination with one or more of the first through eighth aspects, an entropy coding algorithm is a Huffman-coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying a mapping of symbols to binary strings.

In a tenth aspect, alone or in combination with one or more of the first through ninth aspects, the entropy coding algorithm is an arithmetic coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying at least one of a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

In an eleventh aspect, alone or in combination with one or more of the first through tenth aspects, the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

In a twelfth aspect, alone or in combination with one or more of the first through eleventh aspects, the parameter includes information enabling or disabling entropy coding.

In a thirteenth aspect, alone or in combination with one or more of the first through twelfth aspects, the entropy coding configuration information includes a parameter indicating whether entropy coding is applied on a per layer basis of CSI or is applied to all layers of the CSI jointly.

In a fourteenth aspect, alone or in combination with one or more of the first through thirteenth aspects, the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.

In a fifteenth aspect, alone or in combination with one or more of the first through fourteenth aspects, the entropy coding information includes a parameter identifying a payload size for a CSI report included in the CSF message.

In a sixteenth aspect, alone or in combination with one or more of the first through fifteenth aspects, the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

In a seventeenth aspect, alone or in combination with one or more of the first through sixteenth aspects, the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

In an eighteenth aspect, alone or in combination with one or more of the first through seventeenth aspects, the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of CSI or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Although Fig. 7 shows example blocks of process 700, in some aspects, process 700 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 7. Additionally, or alternatively, two or more of the blocks of process 700 may be performed in parallel.

Fig. 8 is a diagram illustrating an example process 800 performed, for example, at a UE or an apparatus of a UE, in accordance with the present disclosure. Example process 800 is an example where the apparatus or the UE (e.g., UE 120 or the apparatus 1300) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 8, in some aspects, process 800 may include receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (block 810) . For example, the UE (e.g., using communication manager 140 and/or reception component 1302, depicted in Fig. 13) may receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof, as described above.

As further shown in Fig. 8, in some aspects, process 800 may include transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters (block 820) . For example, the UE (e.g., using communication manager 140 and/or transmission component 1304, depicted in Fig. 13) may transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters, as described above.

Process 800 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, the entropy coding algorithm is a Huffman-coding algorithm, and wherein the parameter includes information identifying a lookup table mapping of symbols to binary strings.

In a second aspect, alone or in combination with the first aspect, the entropy coding algorithm is an arithmetic coding algorithm, and wherein the parameter includes information identifying at least one of a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

In a third aspect, alone or in combination with one or more of the first and second aspects, the parameter includes information indicating whether entropy coding is applied on a per layer basis of CSI or is applied to all layers of the CSI jointly.

In a fourth aspect, alone or in combination with one or more of the first through third aspects, the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, the parameter includes information enabling or disabling entropy coding.

In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.

Although Fig. 8 shows example blocks of process 800, in some aspects, process 800 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 8. Additionally, or alternatively, two or more of the blocks of process 800 may be performed in parallel.

Fig. 9 is a diagram illustrating an example process 900 performed, for example, at a UE or an apparatus of a UE, in accordance with the present disclosure. Example process 900 is an example where the apparatus or the UE (e.g., UE 120 or the apparatus 1300) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 9, in some aspects, process 900 may include receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (block 910) . For example, the UE (e.g., using communication manager 140 and/or reception component 1302, depicted in Fig. 13) may receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter, as described above.

As further shown in Fig. 9, in some aspects, process 900 may include transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters (block 920) . For example, the UE (e.g., using communication manager 140 and/or transmission component 1304, depicted in Fig. 13) may transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters, as described above.

Process 900 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

In a second aspect, alone or in combination with the first aspect, the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

In a third aspect, alone or in combination with one or more of the first and second aspects, the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of CSI or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Although Fig. 9 shows example blocks of process 900, in some aspects, process 900 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 9. Additionally, or alternatively, two or more of the blocks of process 900 may be performed in parallel.

Fig. 10 is a diagram illustrating an example process 1000 performed, for example, at a network node or an apparatus of a network node, in accordance with the present disclosure. Example process 1000 is an example where the apparatus or the network node (e.g., network node 110 or the apparatus 1800) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 10, in some aspects, process 1000 may include transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF (block 1010) . For example, the network node (e.g., using communication manager 150 and/or transmission component 1804, depicted in Fig. 18) may transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF, as described above.

As further shown in Fig. 10, in some aspects, process 1000 may include receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (block 1020) . For example, the network node (e.g., using communication manager 150 and/or reception component 1802, depicted in Fig. 18) may receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information, as described above.

Process 1000 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

In a first aspect, process 1000 includes receiving UE capability information indicating a capability for entropy coding, and wherein transmitting the entropy coding configuration information comprises transmitting the entropy coding configuration information as a response to transmitting the UE capability information.

In a second aspect, alone or in combination with the first aspect, process 1000 includes transmitting a CSI-RS for measurement, and decoding, in accordance with the entropy coding configuration information and using a decoder, a measurement of the CSI-RS encoded in the CSF message using entropy coding.

Although Fig. 10 shows example blocks of process 1000, in some aspects, process 1000 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 10. Additionally, or alternatively, two or more of the blocks of process 1000 may be performed in parallel.

Fig. 11 is a diagram illustrating an example process 1100 performed, for example, at a network node or an apparatus of a network node, in accordance with the present disclosure. Example process 1100 is an example where the apparatus or the network node (e.g., network node 110 or the apparatus 1800) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 11, in some aspects, process 1100 may include transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (block 1110) . For example, the network node (e.g., using communication manager 150 and/or transmission component 1804, depicted in Fig. 18) may transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof, as described above.

As further shown in Fig. 11, in some aspects, process 1100 may include receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters (block 1120) . For example, the network node (e.g., using communication manager 150 and/or reception component 1802, depicted in Fig. 18) may receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters, as described above.

Process 1100 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

Although Fig. 11 shows example blocks of process 1100, in some aspects, process 1100 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 11. Additionally, or alternatively, two or more of the blocks of process 1100 may be performed in parallel.

Fig. 12 is a diagram illustrating an example process 1200 performed, for example, at a network node or an apparatus of a network node, in accordance with the present disclosure. Example process 1200 is an example where the apparatus or the network node (e.g., network node 110 or the apparatus 1800) performs operations associated with configuration of entropy coding for channel state feedback.

As shown in Fig. 12, in some aspects, process 1200 may include transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (block 1210) . For example, the network node (e.g., using communication manager 150 and/or transmission component 1804, depicted in Fig. 18) may transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter, as described above.

As further shown in Fig. 12, in some aspects, process 1200 may include receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters (block 1220) . For example, the network node (e.g., using communication manager 150 and/or reception component 1802, depicted in Fig. 18) may receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters, as described above.

Process 1200 may include additional aspects, such as any single aspect or any combination of aspects described below and/or in connection with one or more other processes described elsewhere herein.

Although Fig. 12 shows example blocks of process 1200, in some aspects, process 1200 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 12. Additionally, or alternatively, two or more of the blocks of process 1200 may be performed in parallel.

Fig. 13 is a diagram of an example apparatus 1300 for wireless communication, in accordance with the present disclosure. The apparatus 1300 may be a UE, or a UE may include the apparatus 1300. In some aspects, the apparatus 1300 includes a reception component 1302 and a transmission component 1304, which may be in communication with one another (for example, via one or more buses and/or one or more other components) . As shown, the apparatus 1300 may communicate with another apparatus 1306 (such as a UE, a base station, or another wireless communication device) using the reception component 1302 and the transmission component 1304. As further shown, the apparatus 1300 may include the communication manager 140. The communication manager 140 may include one or more of a measurement component 1308, an encoder component 1310, or a vector quantizer component 1312, among other examples.

In some aspects, the apparatus 1300 may be configured to perform one or more operations described herein in connection with Figs. 6A-6F. Additionally, or alternatively, the apparatus 1300 may be configured to perform one or more processes described herein, such as process 700 of Fig. 7, process 800 of Fig. 8, process 900 of Fig. 9, or a combination thereof. In some aspects, the apparatus 1300 and/or one or more components shown in Fig. 13 may include one or more components of the UE described in connection with Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 13 may be implemented within one or more components described in connection with Fig. 2. Additionally, or alternatively, one or more components of the set of components may be implemented at least in part as software stored in one or more memories. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the functions or operations of the component.

The reception component 1302 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 1306. The reception component 1302 may provide received communications to one or more other components of the apparatus 1300. In some aspects, the reception component 1302 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, de-mapping, equalization, interference cancellation, or decoding, among other examples) , and may provide the processed signals to the one or more other components of the apparatus 1300. In some aspects, the reception component 1302 may include one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receive processors, one or more controllers/processors, one or more memories, or a combination thereof, of the UE described in connection with Fig. 2.

The transmission component 1304 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 1306. In some aspects, one or more other components of the apparatus 1300 may generate communications and may provide the generated communications to the transmission component 1304 for transmission to the apparatus 1306. In some aspects, the transmission component 1304 may perform signal processing on the generated communications (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, among other examples) , and may transmit the processed signals to the apparatus 1306. In some aspects, the transmission component 1304 may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers/processors, one or more memories, or a combination thereof, of the UE described in connection with Fig. 2. In some aspects, the transmission component 1304 may be co-located with the reception component 1302 in one or more transceivers.

The reception component 1302 may receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF. The transmission component 1304 may transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

The transmission component 1304 may transmit UE capability information indicating a capability for entropy coding. The reception component 1302 may receive a CSI-RS. The measurement component 1308 may perform a measurement of the CSI-RS. The encoder component 1310 may encode, in accordance with the entropy coding configuration information and using an encoder, the measurement of the CSI-RS using entropy coding to generate at least a portion of the payload of the CSF message. The vector quantization component 1312 may quantize a set of vectors representing data of a CSF message.

The reception component 1302 may receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The transmission component 1304 may transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters. The reception component 1302 may receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The transmission component 1304 may transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

The number and arrangement of components shown in Fig. 13 are provided as an example. In practice, there may be additional components, fewer components, different components, or differently arranged components than those shown in Fig. 13. Furthermore, two or more components shown in Fig. 13 may be implemented within a single component, or a single component shown in Fig. 13 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 13 may perform one or more functions described as being performed by another set of components shown in Fig. 13.

Fig. 14 is a diagram illustrating an example 1400 of a hardware implementation for an apparatus 1405 employing a processing system 1410, in accordance with the present disclosure. The apparatus 1405 may be a UE or may be at (e.g., included in) a UE.

The processing system 1410 may be implemented with a bus architecture, represented generally by the bus 1415. The bus 1415 may include any number of interconnecting buses and bridges depending on the specific application of the processing system 1410 and the overall design constraints. The bus 1415 links together various circuits including one or more processors and/or hardware components, represented by the processor (or processing circuitry) 1420, the illustrated components, and the computer-readable medium/memory (or memory circuitry) 1425. The processor 1420 may include multiple processors, such as processor 1420a, memory 1420b, and memory 1420c. The memory 1425 may include multiple memories, such as memory 1425a, memory 1425b, and memory 1425c. The bus 1415 may also link various other circuits, such as timing sources, peripherals, voltage regulators, and/or power management circuits.

The processing system 1410 may be coupled to one or more transceivers 1430. A transceiver 1430 is coupled to one or more antennas 1435. The transceiver 1430 provides a means for communicating with various other apparatuses over a transmission medium. The transceiver 1430 receives a signal from the one or more antennas 1435, extracts information from the received signal, and provides the extracted information to the processing system 1410, specifically the reception component 1302. In addition, the transceiver 1430 receives information from the processing system 1410, specifically the transmission component 1304, and generates a signal to be applied to the one or more antennas 1435 based at least in part on the received information.

The processing system 1410 includes one or more processors 1420 coupled to a computer-readable medium /memory 1425. A processor 1420 is responsible for general processing, including the execution of software stored on the computer-readable medium /memory 1425. The software, when executed by the processor 1420, causes the processing system 1410 to perform the various functions described herein for any particular apparatus. The computer-readable medium /memory 1425 may also be used for storing data that is manipulated by the processor 1420 when executing software. The processing system further includes at least one of the illustrated components. The components may be software modules running in the processor 1420, resident/stored in the computer readable medium /memory 1425, one or more hardware modules coupled to the processor 1420, or some combination thereof.

In some aspects, the processing system 1410 may be a component of the UE 120 and may include one or more memories, such as the memory 282, and/or may include one or more processors, such as at least one of the TX MIMO processor 266, the RX processor 258, and/or the controller/processor 280. In some aspects, the apparatus 1405 for wireless communication includes means for receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF; and/or means for transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. In some aspects, the apparatus 1405 for wireless communication includes means for receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and/or means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters. In some aspects, the apparatus 1405 for wireless communication includes means for receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and/or means for transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters. The aforementioned means may be one or more of the aforementioned components of the apparatus 1300 and/or the processing system 1410 of the apparatus 1405 configured to perform the functions recited by the aforementioned means. As described elsewhere herein, the processing system 1410 may include the TX MIMO processor 266, the RX processor 258, and/or the controller/processor 280. In one configuration, the aforementioned means may be the TX MIMO processor 266, the RX processor 258, and/or the controller/processor 280 configured to perform the functions and/or operations recited herein.

Fig. 14 is provided as an example. Other examples may differ from what is described in connection with Fig. 14.

Fig. 15 is a diagram illustrating an example 1500 of an implementation of code and circuitry for an apparatus 1505, in accordance with the present disclosure. The circuitry may include processing circuitry and memory circuitry. The apparatus 1505 may be a UE, or a UE may include the apparatus 1505.

As shown in Fig. 15, the apparatus 1505 may include circuitry for receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF (circuitry 1520) . For example, the circuitry 1520 may enable the apparatus 1505 to receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF.

As shown in Fig. 15, the apparatus 1505 may include, stored in computer-readable medium 1425, code for receiving entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF (code 1525) . For example, the code 1525, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to receive entropy coding configuration information identifying one or more fields to include in a payload of a CSF message conveying entropy-coded CSF.

As shown in Fig. 15, the apparatus 1505 may include circuitry for transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (circuitry 1530) . For example, the circuitry 1530 may enable the apparatus 1505 to transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

As shown in Fig. 15, the apparatus 1505 may include, stored in computer-readable medium 1425, code for transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (code 1535) . For example, the code 1535, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Fig. 15 is provided as an example. Other examples may differ from what is described in connection with Fig. 15.

Fig. 16 is a diagram illustrating an example 1600 of an implementation of code and circuitry for an apparatus 1605, in accordance with the present disclosure. The apparatus 1605 may be a UE, or a UE may include the apparatus 1605.

As shown in Fig. 16, the apparatus 1605 may include circuitry for receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (circuitry 1620) . For example, the circuitry 1620 may enable the apparatus 1605 to receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

As shown in Fig. 16, the apparatus 1605 may include, stored in computer-readable medium 1425, code for receiving entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (code 1625) . For example, the code 1625, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to receive entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

As shown in Fig. 16, the apparatus 1605 may include circuitry for transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters (circuitry 1630) . For example, the circuitry 1630 may enable the apparatus 1605 to transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

As shown in Fig. 16, the apparatus 1605 may include, stored in computer-readable medium 1425, code for transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters (code 1635) . For example, the code 1635, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Fig. 16 is provided as an example. Other examples may differ from what is described in connection with Fig. 16.

Fig. 17 is a diagram illustrating an example 1700 of an implementation of code and circuitry for an apparatus 1705, in accordance with the present disclosure. The apparatus 1705 may be a UE, or a UE may include the apparatus 1705.

As shown in Fig. 17, the apparatus 1705 may include circuitry for receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (circuitry 1720) . For example, the circuitry 1720 may enable the apparatus 1705 to receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter.

As shown in Fig. 17, the apparatus 1705 may include, stored in computer-readable medium 1425, code for receiving entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (code 1725) . For example, the code 1725, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to receive entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter.

As shown in Fig. 17, the apparatus 1705 may include circuitry for transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters (circuitry 1730) . For example, the circuitry 1730 may enable the apparatus 1705 to transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

As shown in Fig. 17, the apparatus 1705 may include, stored in computer-readable medium 1425, code for transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters (code 1735) . For example, the code 1735, when executed by processor 1420, may cause processor 1420 to cause transceiver 1430 to transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Fig. 17 is provided as an example. Other examples may differ from what is described in connection with Fig. 17.

Fig. 18 is a diagram of an example apparatus 1800 for wireless communication, in accordance with the present disclosure. The apparatus 1800 may be a network node, or a network node may include the apparatus 1800. In some aspects, the apparatus 1800 includes a reception component 1802 and a transmission component 1804, which may be in communication with one another (for example, via one or more buses and/or one or more other components) . As shown, the apparatus 1800 may communicate with another apparatus 1806 (such as a UE, a base station, or another wireless communication device) using the reception component 1802 and the transmission component 1804. As further shown, the apparatus 1800 may include the communication manager 150. The communication manager 150 may include one or more of a decoder component 1808 or a vector de-quantizer component 1810, among other examples.

In some aspects, the apparatus 1800 may be configured to perform one or more operations described herein in connection with Figs. 6A-6F. Additionally, or alternatively, the apparatus 1800 may be configured to perform one or more processes described herein, such as process 1000 of Fig. 10, process 1100 of Fig. 11, process 1200 of Fig. 12, or a combination thereof. In some aspects, the apparatus 1800 and/or one or more components shown in Fig. 18 may include one or more components of the network node described in connection with Fig. 2. Additionally, or alternatively, one or more components shown in Fig. 18 may be implemented within one or more components described in connection with Fig. 2. Additionally, or alternatively, one or more components of the set of components may be implemented at least in part as software stored in one or more memories. For example, a component (or a portion of a component) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the functions or operations of the component.

The reception component 1802 may receive communications, such as reference signals, control information, data communications, or a combination thereof, from the apparatus 1806. The reception component 1802 may provide received communications to one or more other components of the apparatus 1800. In some aspects, the reception component 1802 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, de-mapping, equalization, interference cancellation, or decoding, among other examples) , and may provide the processed signals to the one or more other components of the apparatus 1800. In some aspects, the reception component 1802 may include one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receive processors, one or more controllers/processors, one or more memories, or a combination thereof, of the network node described in connection with Fig. 2.

The transmission component 1804 may transmit communications, such as reference signals, control information, data communications, or a combination thereof, to the apparatus 1806. In some aspects, one or more other components of the apparatus 1800 may generate communications and may provide the generated communications to the transmission component 1804 for transmission to the apparatus 1806. In some aspects, the transmission component 1804 may perform signal processing on the generated communications (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, among other examples) , and may transmit the processed signals to the apparatus 1806. In some aspects, the transmission component 1804 may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers/processors, one or more memories, or a combination thereof, of the network node described in connection with Fig. 2. In some aspects, the transmission component 1804 may be co-located with the reception component 1802 in one or more transceivers.

The transmission component 1804 may transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF. The reception component 1802 may receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. The reception component 1802 may receive UE capability information indicating a capability for entropy coding. The transmission component 1804 may transmit a CSI-RS for measurement. The decoder component 1808 may decode, in accordance with the entropy coding configuration information and using a decoder, a measurement of the CSI-RS encoded in the CSF message using entropy coding. The vector de-quantizer component 1810 may de-quantize a set of values to recover a set of vectors representing CSF data.

The transmission component 1804 may transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof. The reception component 1802 may receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters. The transmission component 1804 may transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter. The reception component 1802 may receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

The number and arrangement of components shown in Fig. 18 are provided as an example. In practice, there may be additional components, fewer components, different components, or differently arranged components than those shown in Fig. 18. Furthermore, two or more components shown in Fig. 18 may be implemented within a single component, or a single component shown in Fig. 18 may be implemented as multiple, distributed components. Additionally, or alternatively, a set of (one or more) components shown in Fig. 18 may perform one or more functions described as being performed by another set of components shown in Fig. 18.

Fig. 19 is a diagram illustrating an example 1900 of a hardware implementation for an apparatus 1905 employing a processing system 1910, in accordance with the present disclosure. The apparatus 1905 may be a network node or may be at (e.g., included in) a network node.

The processing system 1910 may be implemented with a bus architecture, represented generally by the bus 1915. The bus 1915 may include any number of interconnecting buses and bridges depending on the specific application of the processing system 1910 and the overall design constraints. The bus 1915 links together various circuits including one or more processors and/or hardware components, represented by the processor (or processing circuitry) 1920, the illustrated components, and the computer-readable medium/memory (or memory circuitry) 1925. The processor 1920 may include multiple processors, such as processor 1920a, memory 1920b, and memory 1920c. The memory 1925 may include multiple memories, such as memory 1925a, memory 1925b, and memory 1925c. The bus 1915 may also link various other circuits, such as timing sources, peripherals, voltage regulators, and/or power management circuits.

The processing system 1910 may be coupled to one or more transceivers 1930. A transceiver 1930 is coupled to one or more antennas 1935. The transceiver 1930 provides a means for communicating with various other apparatuses over a transmission medium. The transceiver 1930 receives a signal from the one or more antennas 1935, extracts information from the received signal, and provides the extracted information to the processing system 1910, specifically the reception component 1802. In addition, the transceiver 1930 receives information from the processing system 1910, specifically the transmission component 1804, and generates a signal to be applied to the one or more antennas 1935 based at least in part on the received information.

The processing system 1910 includes one or more processors 1920 coupled to a computer-readable medium /memory 1925. A processor 1920 is responsible for general processing, including the execution of software stored on the computer-readable medium /memory 1925. The software, when executed by the processor 1920, causes the processing system 1910 to perform the various functions described herein for any particular apparatus. The computer-readable medium /memory 1925 may also be used for storing data that is manipulated by the processor 1920 when executing software. The processing system further includes at least one of the illustrated components. The components may be software modules running in the processor 1920, resident/stored in the computer readable medium /memory 1925, one or more hardware modules coupled to the processor 1920, or some combination thereof.

In some aspects, the processing system 1910 may be a component of the network node 110 and may include one or more memories, such as the memory 242, and/or may include one or more processors, such as at least one of the TX MIMO processor 216, the RX processor 238, and/or the controller/processor 240. In some aspects, the apparatus 1905 for wireless communication includes means for transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF; and/or means for receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information. In some aspects, the apparatus 1905 for wireless communication includes means for transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and/or means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters. In some aspects, the apparatus 1905 for wireless communication includes means for transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and/or means for receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters. The aforementioned means may be one or more of the aforementioned components of the apparatus 1800 and/or the processing system 1910 of the apparatus 1905 configured to perform the functions recited by the aforementioned means. As described elsewhere herein, the processing system 1910 may include the TX MIMO processor 216, the receive processor 238, and/or the controller/processor 240. In one configuration, the aforementioned means may be the TX MIMO processor 216, the receive processor 238, and/or the controller/processor 240 configured to perform the functions and/or operations recited herein.

Fig. 19 is provided as an example. Other examples may differ from what is described in connection with Fig. 19.

Fig. 20 is a diagram illustrating an example 2000 of an implementation of code and circuitry for an apparatus 2005, in accordance with the present disclosure. The circuitry may include processing circuitry and memory circuitry. The apparatus 2005 may be a network node, or a network node may include the apparatus 2005.

As shown in Fig. 20, the apparatus 2005 may include circuitry for transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF (circuitry 2020) . For example, the circuitry 2020 may enable the apparatus 2005 to transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF.

As shown in Fig. 20, the apparatus 2005 may include, stored in computer-readable medium 1925, code for transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF (code 2025) . For example, the code 2025, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a CSF message conveying entropy-coded CSF.

As shown in Fig. 20, the apparatus 2005 may include circuitry for receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (circuitry 2030) . For example, the circuitry 2030 may enable the apparatus 2005 to receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

As shown in Fig. 20, the apparatus 2005 may include, stored in computer-readable medium 1925, code for receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information (code 2035) . For example, the code 2035, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Fig. 20 is provided as an example. Other examples may differ from what is described in connection with Fig. 20.

Fig. 21 is a diagram illustrating an example 2100 of an implementation of code and circuitry for an apparatus 2105, in accordance with the present disclosure. The apparatus 2105 may be a network node, or a network node may include the apparatus 2105.

As shown in Fig. 21, the apparatus 2105 may include circuitry for transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (circuitry 2120) . For example, the circuitry 2120 may enable the apparatus 2105 to transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

As shown in Fig. 21, the apparatus 2105 may include, stored in computer-readable medium 1925, code for transmitting entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof (code 2125) . For example, the code 2125, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to transmit entropy coding configuration information identifying one or more parameters for a CSF message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

As shown in Fig. 21, the apparatus 2105 may include circuitry for receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters (circuitry 2130) . For example, the circuitry 2130 may enable the apparatus 2105 to receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

As shown in Fig. 21, the apparatus 2105 may include, stored in computer-readable medium 1925, code for receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters (code 2135) . For example, the code 2135, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Fig. 21 is provided as an example. Other examples may differ from what is described in connection with Fig. 21.

Fig. 22 is a diagram illustrating an example 2200 of an implementation of code and circuitry for an apparatus 2205, in accordance with the present disclosure. The apparatus 2205 may be a network node, or a network node may include the apparatus 2205.

As shown in Fig. 22, the apparatus 2205 may include circuitry for transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (circuitry 2220) . For example, the circuitry 2220 may enable the apparatus 2205 to transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter.

As shown in Fig. 22, the apparatus 2205 may include, stored in computer-readable medium 1925, code for transmitting entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter (code 2225) . For example, the code 2225, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to transmit entropy coding configuration information identifying a set of parameters for a CSF message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter.

As shown in Fig. 22, the apparatus 2205 may include circuitry for receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters (circuitry 2230) . For example, the circuitry 2230 may enable the apparatus 2205 to receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

As shown in Fig. 22, the apparatus 2205 may include, stored in computer-readable medium 1925, code for receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters (code 2235) . For example, the code 2235, when executed by processor 1920, may cause processor 1920 to cause transceiver 1930 to receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Fig. 22 is provided as an example. Other examples may differ from what is described in connection with Fig. 22.

Aspect 1: A method of wireless communication performed at a user equipment (UE) , comprising: receiving entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Aspect 2: The method of Aspect 1, further comprising: transmitting UE capability information indicating a capability for entropy coding; and wherein receiving the entropy coding configuration information comprises: receiving the entropy coding configuration information as a response to transmitting the UE capability information.

Aspect 3: The method of any of Aspects 1-2, further comprising: receiving a channel state information (CSI) reference signal (RS) (CSI-RS) ; performing a measurement of the CSI-RS; and encoding, in accordance with the entropy coding configuration information and using an encoder, the measurement of the CSI-RS using entropy coding to generate at least a portion of the payload of the CSF message; and wherein transmitting the CSF message comprises: transmitting the CSF message to convey the at least the portion of the payload of the CSF message. wherein transmitting the CSF message comprises: transmitting the CSF message to convey the at least the portion of the payload of the CSF message.

Aspect 4: The method of any of Aspects 1-3, wherein the one or more fields include at least one of: a field indicating a parameter relating to a length of an entropy coding output, a field indicating a parameter relating to an entropy coding bypass indication, or a combination thereof.

Aspect 5: The method of Aspect 4, wherein the one or more fields are included in a first part of the CSF message.

Aspect 6: The method of any of Aspects 1-5, wherein the one or more fields include at least one of: a field indicating a parameter relating to a maximum payload across a plurality of layers of a CSF report of the CSF message, a field indicating a parameter relating to an entropy coding output for each layer of the plurality of layers, a field indicating a parameter relating to a total payload across the plurality of layers of the CSF report of the CSF message, or a combination thereof.

Aspect 7: The method of Aspect 6, wherein the one or more fields are included in at least one of a second part of the CSF message or an uplink control information element signaled in connection with the CSF message.

Aspect 8: The method of any of Aspects 1-7, wherein the entropy coding configuration information is signaled via at least one of: a model identification message, a model meta-information message, a radio resource control configuration message, a UE capability signaling message, or a combination thereof.

Aspect 9: The method of any of Aspects 1-8, wherein the entropy coding configuration information includes one or more parameters, the one or more parameters including a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

Aspect 10: The method of any of Aspects 1-9, wherein an entropy coding algorithm is a Huffman-coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying a mapping of symbols to binary strings.

Aspect 11: The method of any of Aspects 1-10, wherein the entropy coding algorithm is an arithmetic coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying at least one of: a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

Aspect 12: The method of Aspect 11, wherein the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

Aspect 13: The method of Aspect 11, wherein the parameter includes information enabling or disabling entropy coding.

Aspect 14: The method of any of Aspects 1-13, wherein the entropy coding configuration information includes a parameter indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.

Aspect 15: The method of Aspect 14, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.

Aspect 16: The method of any of Aspects 1-15, wherein the entropy coding information includes a parameter identifying a payload size for a channel state information (CSI) report included in the CSF message.

Aspect 17: The method of any of Aspects 1-16, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

Aspect 18: The method of any of Aspects 1-17, wherein the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

Aspect 19: The method of Aspect 18, wherein the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of channel state information (CSI) or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Aspect 20: A method of wireless communication performed at a user equipment (UE) , comprising: receiving entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and transmitting the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Aspect 21: The method of Aspect 20, wherein the entropy coding algorithm is a Huffman-coding algorithm, and wherein the parameter includes information identifying a lookup table mapping of symbols to binary strings.

Aspect 22: The method of any of Aspects 20-21, wherein the entropy coding algorithm is an arithmetic coding algorithm, and wherein the parameter includes information identifying at least one of: a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

Aspect 23: The method of any of Aspects 20-22, wherein the parameter includes information indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.

Aspect 24: The method of any of Aspects 20-23, wherein the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

Aspect 25: The method of any of Aspects 20-24, wherein the parameter includes information enabling or disabling entropy coding.

Aspect 26: The method of Aspect 25, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per channel state information (CSI) report basis.

Aspect 27: A method of wireless communication performed at a user equipment (UE) , comprising: receiving entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and transmitting the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Aspect 28: The method of Aspect 27, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

Aspect 29: The method of any of Aspects 27-28, wherein the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

Aspect 30: The method of Aspect 29, wherein the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of channel state information (CSI) or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Aspect 31: A method of wireless communication performed by a network node, comprising: transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Aspect 32: The method of Aspect 31, further comprising: receiving user equipment (UE) capability information indicating a capability for entropy coding; and wherein transmitting the entropy coding configuration information comprises: transmitting the entropy coding configuration information as a response to transmitting the UE capability information.

Aspect 33: The method of any of Aspects 31-32, further comprising: transmitting a channel state information (CSI) reference signal (RS) (CSI-RS) for measurement; and decoding, in accordance with the entropy coding configuration information and using a decoder, a measurement of the CSI-RS encoded in the CSF message using entropy coding.

Aspect 34: The method of any of Aspects 31-33, wherein the one or more fields include at least one of: a field indicating a parameter relating to a length of an entropy coding output, a field indicating a parameter relating to an entropy coding bypass indication, or a combination thereof.

Aspect 35: The method of Aspect 34, wherein the one or more fields are included in a first part of the CSF message.

Aspect 36: The method of any of Aspects 31-35, wherein the one or more fields include at least one of: a field indicating a parameter relating to a maximum payload across a plurality of layers of a CSF report of the CSF message, a field indicating a parameter relating to an entropy coding output for each layer of the plurality of layers, a field indicating a parameter relating to a total payload across the plurality of layers of the CSF report of the CSF message, or a combination thereof.

Aspect 37: The method of Aspect 36, wherein the one or more fields are included in at least one of a second part of the CSF message or an uplink control information element signaled in connection with the CSF message.

Aspect 38: The method of any of Aspects 31-37, wherein the entropy coding configuration information is signaled via at least one of: a model identification message, a model meta-information message, a radio resource control configuration message, a UE capability signaling message, or a combination thereof.

Aspect 39: The method of any of Aspects 31-38, wherein the entropy coding configuration information includes one or more parameters, the one or more parameters including a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof.

Aspect 40: The method of any of Aspects 31-39, wherein an entropy coding algorithm is a Huffman-coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying a mapping of symbols to binary strings.

Aspect 41: The method of any of Aspects 31-40, wherein the entropy coding algorithm is an arithmetic coding algorithm, and wherein the entropy coding configuration information includes a parameter identifying at least one of: a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

Aspect 42: The method of Aspect 41, wherein the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

Aspect 43: The method of Aspect 41, wherein the parameter includes information enabling or disabling entropy coding.

Aspect 44: The method of any of Aspects 31-43, wherein the entropy coding configuration information includes a parameter indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.

Aspect 45: The method of Aspect 44, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.

Aspect 46: The method of any of Aspects 31-45, wherein the entropy coding information includes a parameter identifying a payload size for a channel state information (CSI) report included in the CSF message.

Aspect 47: The method of any of Aspects 31-46, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

Aspect 48: The method of any of Aspects 31-47, wherein the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

Aspect 49: The method of Aspect 48, wherein the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of channel state information (CSI) or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Aspect 50: A method of wireless communication performed by a network node, comprising: transmitting entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and receiving the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Aspect 51: The method of Aspect 50, wherein the entropy coding algorithm is a Huffman-coding algorithm, and wherein the parameter includes information identifying a lookup table mapping of symbols to binary strings.

Aspect 52: The method of any of Aspects 50-51, wherein the entropy coding algorithm is an arithmetic coding algorithm, and wherein the parameter includes information identifying at least one of: a type of the arithmetic coding algorithm, a bitwidth for the arithmetic coding algorithm, an identifier of a termination of an encoding sequence, an indicator of whether to include an end-of-sequence symbol, or a combination thereof.

Aspect 53: The method of any of Aspects 50-52, wherein the parameter includes information indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.

Aspect 54: The method of any of Aspects 50-53, wherein the parameter includes information indicating whether to include an indicator of a length of an entropy coding output or an end-of-sequence symbol in the CSF message.

Aspect 55: The method of any of Aspects 50-54, wherein the parameter includes information enabling or disabling entropy coding.

Aspect 56: The method of Aspect 55, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per channel state information (CSI) report basis.

Aspect 57: A method of wireless communication performed by a network node, comprising: transmitting entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and receiving the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Aspect 58: The method of Aspect 57, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.

Aspect 59: The method of any of Aspects 57-58, wherein the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.

Aspect 60: The method of Aspect 59, wherein the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of channel state information (CSI) or is a single bit indicator for joint encoding of the plurality of layers of CSI.

Aspect 61: An apparatus for wireless communication at a user equipment (UE) , comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the UE to: receive entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Aspect 62: The apparatus of Aspect 61, wherein the one or more processors are configured, individually or collectively, to cause the UE to: receive entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Aspect 63: An apparatus for wireless communication at a user equipment (UE) , comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the UE to: receive receiving entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Aspect 64: The apparatus of Aspect 63, wherein the one or more processors are configured, individually or collectively, to cause the UE to: receive receiving entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and transmit the CSF message to convey the entropy-coded CSF in accordance with the one or more parameters.

Aspect 65: An apparatus for wireless communication at a user equipment (UE) , comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the UE to: receive entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Aspect 66: The apparatus of Aspect 65, wherein the one or more processors are configured, individually or collectively, to cause the UE to: receive entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and transmit the CSF message to convey the entropy-coded CSF in accordance with the set of parameters.

Aspect 67: An apparatus for wireless communication at a network node, comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the network node to: transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.

Aspect 68: The apparatus of Aspect 67, wherein the one or more processors are configured, individually or collectively, to cause the network node to: transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information

Aspect 69: An apparatus for wireless communication at a network node, comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the network node to: transmit entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Aspect 70: The apparatus of Aspect 69, wherein the one or more processors are configured, individually or collectively, to cause the network node to: transmit entropy coding configuration information identifying one or more parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the one or more parameters includes a parameter identifying at least one of: an entropy coding algorithm, a probability mass function, whether the probability mass function is used over entries of an embedding vector, or a combination thereof; and receive the CSF message that conveys the entropy-coded CSF in accordance with the one or more parameters.

Aspect 71: An apparatus for wireless communication at a network node, comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured to cause the network node to: transmit entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Aspect 72: The apparatus of Aspect 71, wherein the one or more processors are configured, individually or collectively, to cause the network node to: transmit entropy coding configuration information identifying a set of parameters for a channel state feedback (CSF) message conveying entropy-coded CSF, wherein the set of parameters includes a payload size parameter; and receive the CSF message that conveys the entropy-coded CSF in accordance with the set of parameters.

Aspect 73: An apparatus for wireless communication at a device, the apparatus comprising one or more processors; one or more memories coupled with the one or more processors; and instructions stored in the one or more memories and executable by the one or more processors to cause the apparatus to perform the method of one or more of Aspects 1-72.

Aspect 74: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors configured to cause the device to perform the method of one or more of Aspects 1-72.

Aspect 75: An apparatus for wireless communication, the apparatus comprising at least one means for performing the method of one or more of Aspects 1-60.

Aspect 76: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by one or more processors to perform the method of one or more of Aspects 1-72.

Aspect 77: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method of one or more of Aspects 1-72.

Aspect 78: A device for wireless communication, the device comprising a processing system that includes one or more processors and one or more memories coupled with the one or more processors, the processing system configured to cause the device to perform the method of one or more of Aspects 1-72.

Aspect 79: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors individually or collectively configured to cause the device to perform the method of one or more of Aspects 1-72.

The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the aspects to the precise forms disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the aspects.

As used herein, the term “component” is intended to be broadly construed as hardware or a combination of hardware and at least one of software or firmware. “Software” shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, or functions, among other examples, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. As used herein, a “processor” is implemented in hardware or a combination of hardware and software. It will be apparent that systems or methods described herein may be implemented in different forms of hardware or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems or methods is not limiting of the aspects. Thus, the operation and behavior of the systems or methods are described herein without reference to specific software code, because those skilled in the art will understand that software and hardware can be designed to implement the systems or methods based, at least in part, on the description herein. A component being configured to perform a function means that the component has a capability to perform the function, and does not require the function to be actually performed by the component, unless noted otherwise.

As used herein, “satisfying a threshold” may, depending on the context, refer to a value being greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, or not equal to the threshold, among other examples.

As used herein, a phrase referring to “at least one of” a list of items refers to any combination of those items, including single members. As an example, “at least one of: a, b, or c” is intended to cover a, b, c, a + b, a + c, b + c, and a + b + c, as well as any combination with multiples of the same element (for example, a + a, a + a + a, a + a + b, a + a + c, a + b + b, a + c + c, b + b, b + b + b, b + b + c, c + c, and c + c + c, or any other ordering of a, b, and c) .

No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more. ” Further, as used herein, the article “the” is intended to include one or more items referenced in connection with the article “the” and may be used interchangeably with “the one or more. ” Furthermore, as used herein, the terms “set” and “group” are intended to include one or more items and may be used interchangeably with “one or more. ” Where only one item is intended, the phrase “only one” or similar language is used. Also, as used herein, the terms “has, ” “have, ” “having, ” and similar terms are intended to be open-ended terms that do not limit an element that they modify (for example, an element “having” A may also have B) . Further, the phrase “based on” is intended to mean “based on or otherwise in association with” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and/or, ” unless explicitly stated otherwise (for example, if used in combination with “either” or “only one of” ) . It should be understood that “one or more” is equivalent to “at least one. ”

Even though particular combinations of features are recited in the claims or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. Many of these features may be combined in ways not specifically recited in the claims or disclosed in the specification. The disclosure of various aspects includes each dependent claim in combination with every other claim in the claim set.

Claims

An apparatus for wireless communication at a user equipment (UE) , comprising:

one or more memories; and

one or more processors, coupled with the one or more memories and configured to cause the UE to:

receive entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and

transmit the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.
The apparatus of claim 1, wherein the one or more processors are further configured to cause the UE to:

transmit UE capability information indicating a capability for entropy coding; and

wherein the one or more processors, to cause the UE to receive the entropy coding configuration information, are configured to cause the UE to:

receive the entropy coding configuration information as a response to transmitting the UE capability information.
The apparatus of claim 1, wherein the one or more processors are further configured to cause the UE to:

receive a channel state information (CSI) reference signal (RS) (CSI-RS) ;

perform a measurement of the CSI-RS; and

encode, in accordance with the entropy coding configuration information and using an encoder, the measurement of the CSI-RS using entropy coding to generate at least a portion of the payload of the CSF message; and

wherein the one or more processors, to cause the UE to transmit the CSF message, are configured to cause the UE to:

transmit the CSF message to convey the at least the portion of the payload of the CSF message.
The apparatus of claim 1, wherein the one or more fields include at least one of:

a field indicating a parameter relating to a length of an entropy coding output,

a field indicating a parameter relating to an entropy coding bypass indication, or

a combination thereof.
The apparatus of claim 4, wherein the one or more fields are included in a first part of the CSF message.
The apparatus of claim 1, wherein the one or more fields include at least one of:

a field indicating a parameter relating to a maximum payload across a plurality of layers of a CSF report of the CSF message,

a field indicating a parameter relating to an entropy coding output for each layer of the plurality of layers,

a field indicating a parameter relating to a total payload across the plurality of layers of the CSF report of the CSF message, or

a combination thereof.
The apparatus of claim 6, wherein the one or more fields are included in at least one of a second part of the CSF message or an uplink control information element signaled in connection with the CSF message.
The apparatus of claim 1, wherein the entropy coding configuration information is signaled via at least one of:

a model identification message,

a model meta-information message,

a radio resource control configuration message,

a UE capability signaling message, or

a combination thereof.
The apparatus of claim 1, wherein the entropy coding configuration information includes one or more parameters, the one or more parameters including a parameter identifying at least one of:

an entropy coding algorithm,

a probability mass function,

whether the probability mass function is used over entries of an embedding vector, or

a combination thereof.
The apparatus of claim 1, wherein the entropy coding configuration information includes a parameter indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.
The apparatus of claim 10, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.
The apparatus of claim 1, wherein the entropy coding information includes a parameter identifying a payload size for a channel state information (CSI) report included in the CSF message.
The apparatus of claim 1, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.
The apparatus of claim 1, wherein the CSF message includes a greedy-bypass of an entropy coding output for the CSF message and an indicator of the CSF message including the greedy-bypass of the entropy coding output.
The apparatus of claim 14, wherein the indicator of the CSF message including the greedy-bypass of the entropy coding output is a plurality of bit indicators for separate encoding of a plurality of layers of channel state information (CSI) or is a single bit indicator for joint encoding of the plurality of layers of CSI.
An apparatus for wireless communication at a network node, comprising:

one or more memories; and

one or more processors coupled with the one or more memories and configured to cause the network node to:

transmit entropy coding configuration information identifying one or more fields for inclusion in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and

receive the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.
The apparatus of claim 16, wherein the one or more processors are further configured to cause the network node to:

receive user equipment (UE) capability information indicating a capability for entropy coding; and

wherein the one or more processors, to cause the network node to transmit the entropy coding configuration information, are configured to cause the network node to:

transmit the entropy coding configuration information as a response to transmitting the UE capability information.
The apparatus of claim 16, wherein the one or more processors are further configured to cause the network node to:

transmit a channel state information (CSI) reference signal (RS) (CSI-RS) for measurement; and

decode, in accordance with the entropy coding configuration information and using a decoder, a measurement of the CSI-RS encoded in the CSF message using entropy coding.
The apparatus of claim 16, wherein the one or more fields include at least one of:

a field indicating a parameter relating to a length of an entropy coding output,

a field indicating a parameter relating to an entropy coding bypass indication, or

a combination thereof.
The apparatus of claim 19, wherein the one or more fields are included in a first part of the CSF message.
The apparatus of claim 16, wherein the one or more fields include at least one of:

a field indicating a parameter relating to a maximum payload across a plurality of layers of a CSF report of the CSF message,

a field indicating a parameter relating to an entropy coding output for each layer of the plurality of layers,

a field indicating a parameter relating to a total payload across the plurality of layers of the CSF report of the CSF message, or

a combination thereof.
The apparatus of claim 21, wherein the one or more fields are included in at least one of a second part of the CSF message or an uplink control information element signaled in connection with the CSF message.
The apparatus of claim 16, wherein the entropy coding configuration information is signaled via at least one of:

a model identification message,

a model meta-information message,

a radio resource control configuration message,

a UE capability signaling message, or

a combination thereof.
The apparatus of claim 16, wherein the entropy coding configuration information includes one or more parameters, the one or more parameters including a parameter identifying at least one of:

an entropy coding algorithm,

a probability mass function,

whether the probability mass function is used over entries of an embedding vector, or

a combination thereof.
The apparatus of claim 16, wherein the entropy coding configuration information includes a parameter indicating whether entropy coding is applied on a per layer basis of channel state information (CSI) or is applied to all layers of the CSI jointly.
The apparatus of claim 25, wherein the parameter is an adaptive entropy coding bypass parameter on a per layer or per CSI report basis.
The apparatus of claim 16, wherein the entropy coding information includes a parameter identifying a payload size for a channel state information (CSI) report included in the CSF message.
The apparatus of claim 16, wherein the entropy coding configuration information includes an indication of whether to use a greedy-bypass of an entropy coding output for the CSF message.
A method of wireless communication performed at a user equipment (UE) , comprising:

receiving entropy coding configuration information identifying one or more fields to include in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and

transmitting the CSF message to convey the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.
A method of wireless communication performed at a network node, comprising:

transmitting entropy coding configuration information identifying one or more fields for inclusion in a payload of a channel state feedback (CSF) message conveying entropy-coded CSF; and

receiving the CSF message that conveys the entropy-coded CSF, the CSF message including the one or more fields in accordance with the entropy coding configuration information.