WO2025179534A1

WO2025179534A1 - Ue-centric ai/ml enhancements for ltm

Info

Publication number: WO2025179534A1
Application number: PCT/CN2024/079318
Authority: WO
Inventors: Fangli Xu; Alexander Sirotkin; Naveen Kumar R Palle VENKATA; Haijing Hu; Ping-Heng Kuo; Peng Cheng; Ralf ROSSBACH; Zhibin Wu
Original assignee: Apple Inc
Current assignee: Apple Inc
Priority date: 2024-02-29
Filing date: 2024-02-29
Publication date: 2025-09-04
Anticipated expiration: 2026-08-29

Abstract

A method of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a user equipment (UE) using an artificial intelligence (AI) model is disclosed. The method comprises sending a measurement report from the UE to a base station using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report; receiving a RRC reconfiguration message from the base station that includes an LTM candidate cell configuration list; sending an RRC reconfiguration complete message from the UE to the base station; determining an enhancement to the LTM based on an inference output from the AI model at the UE; and executing a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.

Description

UE-CENTRIC AI/ML ENHANCEMENTS FOR LTM

FIELD

Embodiments of the invention relate to wireless communications, including apparatuses, systems, and methods to facilitate UE-centric AI/ML enhancements for lower layer triggered mobility (LTM) .

DESCRIPTION OF THE RELATED ART

Wireless communication systems are rapidly growing in usage. In recent years, wireless devices such as smart phones and tablet computers have become increasingly sophisticated. In addition to supporting telephone calls, many mobile devices now provide access to the internet, email, text messaging, and navigation using the global positioning system (GPS) and are capable of operating sophisticated applications that utilize these functionalities.

Long Term Evolution (LTE) has been the technology of choice for the majority of wireless network operators worldwide, providing mobile broadband data and high-speed Internet access to their subscriber base. LTE was first proposed in 2004 and was first standardized in 2008. Since then, as usage of wireless communication systems has expanded exponentially, demand has risen for wireless network operators to support a higher capacity for a higher density of mobile broadband users. In 2015, a study of a new radio access technology began and, in 2017, a first release of Fifth Generation New Radio (5G NR) was standardized.

5G-NR, also simply referred to as NR, provides, as compared to LTE, a higher capacity for a higher density of mobile broadband users, while also supporting device-to-device, ultra-reliable, and massive machine type communications with lower latency and/or lower battery consumption. Further, NR may allow for more flexible scheduling as compared to current LTE. Consequently, efforts are being made in ongoing developments of NR to take advantage of higher throughputs possible at higher frequencies..

SUMMARY

Embodiments related to wireless communications, and more particularly to methods of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a user equipment (UE) using an artificial intelligence (AI) model are disclosed. A method comprises sending a measurement report from the UE to a base station using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report; receiving a RRC reconfiguration message from the base station that includes an LTM candidate cell configuration list; sending an RRC reconfiguration complete message from the UE to the base station; determining an enhancement to the LTM based on an inference output from the AI model at the UE; and executing a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.

The techniques described herein may be implemented in and/or used with a number of different types of devices, including but not limited to unmanned aerial vehicles (UAVs) , unmanned aerial controllers (UACs) , base stations, access points, cellular phones, tablet computers, wearable computing devices, portable media players, internet of things (IOT) and any of various other computing devices.

This Summary is intended to provide a brief overview of some of the subject matter described in this document. Accordingly, it will be appreciated that the above-described features are merely examples and should not be construed to narrow the scope or spirit of the subject matter described herein in any way. Other features, aspects, and advantages of the subject matter described herein will become apparent from the following Detailed Description, Figures, and Claims.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the present subject matter can be obtained when the following detailed description of various embodiments is considered in conjunction with the following drawings, in which:

FIG. 1A illustrates an example wireless communication system according to some embodiments.

FIG. 1 B illustrates an example of a base station and an access point in communication with a user equipment (UE) device, according to some embodiments.

FIG. 2 illustrates an example block diagram of a base station, according to some embodiments.

FIG. 3 illustrates an example block diagram of a server according to some embodiments.

FIG. 4 illustrates an example block diagram of a UE according to some embodiments.

FIG. 5 illustrates an example block diagram of cellular communication circuitry, according to some embodiments.

FIG. 6 illustrates an example of a baseband processor architecture for a UE, according to some embodiments.

FIG. 7 illustrates an example block diagram of an interface of baseband circuitry according to some embodiments.

FIG. 8 illustrates an example of a control plane protocol stack in accordance with some embodiments.

FIG. 9 illustrates an example of a user plane protocol stack in accordance with some embodiments.

FIG. 10 illustrates example components of a core network in accordance with some embodiments.

FIG. 11A illustrates an example of a diagram illustrating beamforming using Layer 3 in accordance with some embodiments.

FIG. 11 B illustrates an example of a diagram illustrating beamforming using Layer 1 in accordance with some embodiments.

FIG. 12 illustrates an example flowchart of a legacy Layer 1 /Layer 2 Triggered Mobility (LTM) process in accordance with some embodiments.

FIG. 13 illustrates an example of a generic AI/ML model operational workflow for an AI Model in accordance with some embodiments.

FIG. 14 illustrates an example of an LTM process enhanced with an AI model configured to determine LTM candidate cells that operate above a selected performance threshold in accordance with some embodiments.

FIG. 15 illustrates an example of an LTM process enhanced with an AI model configured to infer when LTM cell switching will occur in accordance with some embodiments.

FIG. 16 illustrates an example of an LTM process enhanced with an AI model configured to infer a transmission control indicator (TCI) state to activate for an LTM candidate cell in accordance with some embodiments.

FIG. 17 illustrates an example of an LTM process enhanced with an AI model configured to infer for which cells early timing advance (TA) acquisition can be configured by the network in accordance with some embodiments.

FIG. 18 illustrates an example of an LTM process enhanced with an AI model configured to infer when a Layer 3 (L3) handover or an LTM would be should be selected for a UE in accordance with some embodiments.

FIG. 19 illustrates an example method of enhancing LTM at a UE using an artificial intelligence (AI) model in accordance with some embodiments.

While the features described herein may be susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are herein described in detail. It should be understood, however, that the drawings and detailed description thereto are not intended to be limiting to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the subject matter as defined by the appended claims.

DETAILED DESCRIPTION

Terms

The following is a glossary of terms used in this disclosure:

Memory Medium or Memory –Any of various types of non-transitory memory devices or storage devices. The term “memory medium” is intended to include an installation medium, e.g., a CD-ROM, floppy disks, or tape device; a computer system memory or random-access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc. ; a non-volatile memory such as a Flash, magnetic media, e.g., a hard drive, or optical storage; registers, or other similar types of memory elements, etc. The memory medium may include other types of non-transitory memory as well or combinations thereof. In addition, the memory medium may be located in a first computer system in which the programs are executed, or may be located in a second different computer system which connects to the first computer system over a network, such as the Internet. In the latter instance, the second computer system may provide program instructions to the first computer for execution. The term “memory medium” may include two or more memory mediums which may reside in different locations, e.g., in different computer systems that are connected over a network. The memory medium may store program instructions (e.g., embodied as computer programs) that may be executed by one or more processors.

Carrier Medium –a memory medium as described above, as well as a physical transmission medium, such as a bus, network, and/or other physical transmission medium that conveys signals such as electrical, electromagnetic, or digital signals.

Programmable Hardware Element includes various hardware devices comprising multiple programmable function blocks connected via a programmable interconnect. Examples include FPGAs (Field Programmable Gate Arrays) , PLDs (Programmable Logic Devices) , FPOAs (Field Programmable Object Arrays) , and CPLDs (Complex PLDs) . The programmable function blocks may range from fine grained (combinatorial logic or look up tables) to coarse grained (arithmetic logic units or processor cores) . A programmable hardware element may also be referred to as "reconfigurable logic” .

Computer System (or Computer) –any of various types of computing or processing systems, including a personal computer system (PC) , mainframe computer system, workstation, network appliance, Internet appliance, personal digital assistant (PDA) , television system, grid computing system, or other device or combinations of devices. In general, the term "computer system" can be broadly defined to encompass any device (or combination of devices) having at least one processor that executes instructions from a memory medium.

User Equipment (UE) (or “UE Device” ) –any of various types of computer systems devices which are mobile or portable and which performs wireless communications. Examples of UE devices include mobile telephones or smart phones (e.g., iPhone^TM, Android^TM-based phones) , portable gaming devices (e.g., Nintendo DS^TM, PlayStation Portable^TM, Gameboy Advance^TM, iPhone^TM) , laptops, wearable devices (e.g., smart watch, smart glasses) , PDAs, portable Internet devices, Internet of Things, music players, data storage devices, other handheld devices, unmanned aerial vehicles (UAVs) (e.g., drones) , UAV controllers (UACs) , and so forth. In general, the term “UE” or “UE device” can be broadly defined to encompass any electronic, computing, and/or telecommunications device (or combination of devices) which is easily transported by a user and capable of wireless communication.

Base Station –The term “Base Station” has the full breadth of its ordinary meaning, and at least includes a wireless communication station installed at a fixed location and used to communicate with UEs as part of a wireless telephone system or radio system, including but not limited Next Generation Node-Bs (gNB or gNodeB) in NR.

LTM –refers to lower layer triggered mobility or Layer 1 /Layer 2 Triggered Mobility in which the UE is configured to perform L1 measurements on a neighbor cell.

Processing Element (or Processor) –refers to various elements or combinations of elements that are capable of performing a function in a device, such as a user equipment or a cellular network device. Processing elements may include, for example: processors and associated memory, portions or circuits of individual processor cores, entire processor cores, processor arrays, circuits such as an ASIC (Application Specific Integrated Circuit) , programmable hardware elements such as a field programmable gate array (FPGA) , as well any of various combinations of the above.

Channel -a medium used to convey information from a sender (transmitter) to a receiver. It should be noted that since characteristics of the term “channel” may differ according to different wireless protocols, the term “channel” as used herein may be considered as being used in a manner that is consistent with the standard of the type of device with reference to which the term is used. In some standards, channel widths may be variable (e.g., depending on device capability, band conditions, etc. ) . For example, LTE may support scalable channel bandwidths from 1.4 MHz to 20MHz. 5G NR can support scalable channel bandwidths from 5 MHz to 100 MHz in Frequency Range 1 (FR1) and up to 400 MHz in FR2. In other radio access technologies, WLAN channels may be 22 MHz wide while Bluetooth channels may be 1 MHz wide. Other protocols and standards may include different definitions of channels. Furthermore, some standards may define and use multiple types of channels, e.g., different channels for uplink or downlink and/or different channels for different uses such as data, control information, etc.

Band -The term "band" has the full breadth of its ordinary meaning, and at least includes a section of spectrum (e.g., radio frequency spectrum) in which channels are used or set aside for the same purpose.

Automatically –refers to an action or operation performed by a computer system (e.g., software executed by the computer system) or device (e.g., circuitry, programmable hardware elements, ASICs, etc. ) , without user input directly specifying or performing the action or operation. Thus, the term "automatically" is in contrast to an operation being manually performed or specified by the user, where the user provides input to directly perform the operation. An automatic procedure may be initiated by input provided by the user, but the subsequent actions that are performed “automatically” are not specified by the user, i.e., are not performed “manually” , where the user specifies each action to perform. For example, a user filling out an electronic form by selecting each field and providing input specifying information (e.g., by typing information, selecting check boxes, radio selections, etc. ) is filling out the form manually, even though the computer system will update the form in response to the user actions. The form may be automatically filled out by the computer system where the computer system (e.g., software executing on the computer system) analyzes the fields of the form and fills in the form without any user input specifying the answers to the fields. As indicated above, the user may invoke the automatic filling of the form, but is not involved in the actual filling of the form (e.g., the user is not manually specifying answers to fields but rather they are being automatically completed) . The present specification provides various examples of operations being automatically performed in response to actions the user has taken.

Approximately -refers to a value that is almost correct or exact. For example, approximately may refer to a value that is within 1 to 10 percent of the exact (or desired) value. It should be noted, however, that the actual threshold value (or tolerance) may be application dependent. For example, in some embodiments, “approximately” may mean within 0.1%of some specified or desired value, while in various other embodiments, the threshold may be, for example, 2%, 3%, 5%, and so forth, as desired or as set by the particular application.

Concurrent –refers to parallel execution or performance, where tasks, processes, or programs are performed in an at least partially overlapping manner. For example, concurrency may be implemented using “strong” or strict parallelism, where tasks are performed (at least partially) in parallel on respective computational elements, or using “weak parallelism” , where the tasks are performed in an interleaved manner, e.g., by time multiplexing of execution threads.

Information Element –a group of information that may be included within a Signaling Message or Data Flow which is sent across an interface.

Legacy -The 3rd Generation Partnership Project (3GPP) produces specifications that define 3GPP technologies. 3GPP specifications cover cellular telecommunications technologies, including radio access, core network and service capabilities, which provide a complete system description for mobile telecommunications. 3GPP uses a system of parallel “Releases” that provide developers with a stable platform for the implementation of features at a given point and then allow for the addition of new functionality in subsequent releases. Release 17 was released in 2022. Release 18 (Rel-18) , at the time of this disclosure, is nearing release as its specifications have been largely defined. Accordingly, implementations and concepts compatible with Rel-18, or previous Releases, are sometimes referred to herein as “Legacy. ” One or more embodiments of the present disclosure may be adopted in future Releases, e.g., Release 19.

rN –As used herein rN, when used in conjunction with an Information Element (IE) refers to a UE that is capable of supporting 3GPP Release N. For example, r19, in associated with the IE, denotes an IE configured for a UE capable of supporting 3GPP release 19. A UE that is capable of supporting a release greater than N may also be capable of supporting 3GPP Release N. A UE that is not capable of supporting 3GPP Release N may not be capable of supporting the IEs that include rN.

AI/ML-enabled Feature: refers to a Feature where AI/ML may be used.

AI/ML Model: A data driven algorithm that applies AI/ML techniques to generate a set of outputs based on a set of inputs.

AI/ML model delivery: A generic term referring to delivery of an AI/ML model from one entity to another entity in any manner. Note: An entity could mean a network node/function (e.g., gNB, LMF, etc. ) , UE, proprietary server, etc.

AI/ML model Inference: A process of using a trained AI/ML model to produce a set of outputs based on a set of inputs.

AI/ML model testing: A subprocess of training, to evaluate the performance of a final AI/ML model using a dataset different from one used for model training and validation. Differently from AI/ML model validation, testing does not assume subsequent tuning of the model.

AI/ML model training: A process to train an AI/ML Model [by learning the input/output relationship] in a data driven manner and obtain the trained AI/ML Model for inference.

AI/ML model transfer: Delivery of an AI/ML model over the air interface in a manner that is not transparent to 3GPP signaling, either parameters of a model structure known at the receiving end or a new model with parameters. Delivery may contain a full model or a partial model.

AI/ML model validation: A subprocess of training, to evaluate the quality of an AI/ML model using a dataset different from one used for model training, that helps selecting model parameters that generalize beyond the dataset used for model training.

Data collection: A process of collecting data by the network nodes, management entity, or UE for the purpose of AI/ML model training, data analytics and inference.

Model activation: enable an AI/ML model for a specific AI/ML-enabled feature.

Model deactivation: disable an AI/ML model for a specific AI/ML-enabled feature.

Model download: Model transfer from the network to UE.

Model identification: A process/method of identifying an AI/ML model for the common understanding between the NW and the UE. Note: The process/method of model identification may or may not be applicable. Note: Information regarding the AI/ML model may be shared during model identification.

Model monitoring: A procedure that monitors the inference performance of the AI/ML model.

Model parameter update: Process of updating the model parameters of a model.

Model selection: The process of selecting an AI/ML model for activation among multiple models for the same AI/ML enabled feature. Note: Model selection may or may not be carried out simultaneously with model activation.

Model switching: Deactivating a currently active AI/ML model and activating a different AI/ML model for a specific AI/ML-enabled feature.

Model update: Process of updating the model parameters and/or model structure of a model.

Model upload: Model transfer from UE to the network.

Network-side (AI/ML) model: An AI/ML Model whose inference is performed entirely at the network.

Offline field data: The data collected from field and used for offline training of the AI/ML model.

Offline training: An AI/ML training process where the model is trained based on collected dataset, and where the trained model is later used or delivered for inference. Note: This definition only serves as a guidance. There may be cases that may not exactly conform to this definition but could still be categorized as offline training by commonly accepted conventions.

Online field data: The data collected from field and used for online training of the AI/ML model.

Online training: An AI/ML training process where the model being used for inference) is (typically continuously) trained in (near) real-time with the arrival of new training samples. Note: the notion of (near) real-time vs. non real-time.

UE-side (AI/ML) model: An AI/ML Model whose inference is performed entirely at the UE.

Unsupervised learning: A process of training a model without labelled data.

Proprietary-format models: ML models of vendor-/device-specific proprietary format, from 3GPP perspective. They are not mutually recognizable across vendors and hide model design information from other vendors when shared. Note: An example is a device-specific binary executable format.

Open-format models: ML models of specified format that are mutually recognizable across vendors and allow interoperability, from 3GPP perspective. They are mutually recognizable between vendors and do not hide model design information from other vendors when shared.

Various components may be described as “configured to” perform a task or tasks. In such contexts, “configured to” is a broad recitation generally meaning “having structure that” performs the task or tasks during operation. As such, the component can be configured to perform the task even when the component is not currently performing that task (e.g., a set of electrical conductors may be configured to electrically connect a module to another module, even when the two modules are not connected) . In some contexts, “configured to” may be a broad recitation of structure generally meaning “having circuitry that” performs the task or tasks during operation. As such, the component can be configured to perform the task even when the component is not currently on. In general, the circuitry that forms the structure corresponding to “configured to” may include hardware circuits.

Various components may be described as performing a task or tasks, for convenience in the description. Such descriptions should be interpreted as including the phrase “configured to. ” Reciting a component that is configured to perform one or more tasks is expressly intended not to invoke 35 U. S. C. § 112 (f) interpretation for that component.

The example embodiments may be further understood with reference to the following description and the related appended drawings, wherein like elements are provided with the same reference numerals. The example embodiments relate to apparatuses, systems and method for reducing energy usage by network components, e.g., base stations in wireless communication systems.

The example embodiments are described with regard to communication between a Next Generation Node B (gNB) and a user equipment (UE) . However, reference to a gNB or a UE is merely provided for illustrative purposes. The example embodiments may be utilized with any electronic component that may establish a connection to a network and is configured with the hardware, software, and/or firmware to support for reducing energy usage by network components in wireless communication systems. Therefore, the gNB or UE as described herein is used to represent any appropriate type of electronic component.

The example embodiments are also described with regard to a fifth generation (5G) New Radio (NR) network that may configure a UE to support for reducing energy usage by network components in wireless communication systems. However, reference to a 5G NR network is merely provided for illustrative purposes. The example embodiments may be utilized with any appropriate type of network.

Throughout this description various information elements (IEs) are referred to by specific names. It should be understood that these names are only examples and the IEs carrying the information referred to throughout this description may be referred to by other names by various entities.

Figures 1A and 1B: Communication Systems

FIG. 1A illustrates a simplified example wireless communication system, according to some embodiments. It is noted that the system of FIG. 1A is merely one example of a possible system, and that features of this disclosure may be implemented in any of various systems, as desired.

As shown, the example wireless communication system includes a base station 102A which communicates over a transmission medium with one or more user devices 106A, 106B, etc., through 106N. Each of the user devices may be referred to herein as a “user equipment” (UE) . Thus, the user devices 106 are referred to as UEs or UE devices.

The base station (BS) 102A may be a base transceiver station (BTS) or cell site (a “cellular base station” ) and may include hardware that enables wireless communication with the UEs 106A through 106N.

The communication area (or coverage area) of the base station may be referred to as a “cell. ” The base station 102A and the UEs 106 may be configured to communicate over the transmission medium using any of various radio access technologies (RATs) , also referred to as wireless communication technologies, or telecommunication standards, such as GSM, UMTS (associated with, for example, WCDMA or TD-SCDMA air interfaces) , LTE, LTE-Advanced (LTE-A) , 5G new radio (5G NR) , HSPA, 3GPP2 CDMA2000 (e.g., 1xRTT, 1xEV-DO, HRPD, eHRPD) , etc. Note that if the base station 102A is implemented in the context of LTE, also referred to as the Evolved Universal Terrestrial Radio Access Network (E-UTRAN, it may alternately be referred to as an 'eNodeB'or ‘eNB’ . Note that if the base station 102A is implemented in the context of 5G NR, it may alternately be referred to as ‘gNodeB’ or ‘gNB’ .

As shown, the base station 102A may also be equipped to communicate with a network 100 (e.g., a core network of a cellular service provider, a telecommunication network such as a public switched telephone network (PSTN) , and/or the Internet, among various possibilities) . Thus, the base station 102A may facilitate communication between the user devices and/or between the user devices and the network 100. In particular, the cellular base station 102A may provide UEs 106 with various telecommunication capabilities, such as voice, SMS and/or data services.

Base station 102A and other similar base stations (such as base stations 102B…102N) operating according to the same or a different cellular communication standard may thus be provided as a network of cells, which may provide continuous or nearly continuous overlapping service to UEs 106A-N and similar devices over a geographic area via one or more cellular communication standards.

Thus, while base station 102A may act as a “serving cell” for UEs 106A-N as illustrated in FIG. 1A, each UE 106 may also be capable of receiving signals from (and possibly within communication range of) one or more other cells (which might be provided by base stations 102B-N and/or any other base stations) , which may be referred to as “neighboring cells” . Such cells may also be capable of facilitating communication between user devices and/or between user devices and the network 100. Such cells may include “macro” cells, “micro” cells, “pico” cells, and/or cells which provide any of various other granularities of service area size. For example, base stations 102A-B illustrated in FIG. 1A might be macro cells, while base station 102N might be a micro cell. Other configurations are also possible.

In some embodiments, base station 102A may be a next generation base station, e.g., a 5G New Radio (5G NR) base station, or “gNB” . In some embodiments, a gNB may be connected to a legacy evolved packet core (EPC) network and/or to a NR core (NRC) network. In addition, a gNB cell may include one or more transition and reception points (TRPs) . In addition, a UE capable of operating according to 5G NR may be connected to one or more TRPs within one or more gNBs.

Note that a UE 106 may be capable of communicating using multiple wireless communication standards. For example, the UE 106 may be configured to communicate using a wireless networking (e.g., Wi-Fi) and/or peer-to-peer wireless communication protocol (e.g., Bluetooth, Wi-Fi peer-to-peer, etc. ) in addition to at least one cellular communication protocol (e.g., GSM, UMTS (associated with, for example, WCDMA or TD-SCDMA air interfaces) , LTE, LTE-A, 5G NR, HSPA, 3GPP2 CDMA2000 (e.g., 1xRTT, 1xEV-DO, HRPD, eHRPD) , etc. ) . The UE 106 may also or alternatively be configured to communicate using one or more global navigational satellite systems (GNSS, e.g., GPS or GLONASS) , one or more mobile television broadcasting standards (e.g., ATSC-M/H or DVB-H) , and/or any other wireless communication protocol, if desired. Other combinations of wireless communication standards (including more than two wireless communication standards) are also possible.

FIG. 1 B illustrates user equipment 106 (e.g., one of the devices 106A through 106N) in communication with a base station 102 and an access point 112, according to some embodiments. The UE 106 may be a device with both cellular communication capability and non-cellular communication capability (e.g., Bluetooth, Wi-Fi, and so forth) such as a mobile phone, a hand-held device, a computer or a tablet, or virtually any type of wireless device.

The UE 106 may include a processor that is configured to execute program instructions stored in memory. The UE 106 may perform any of the method embodiments described herein by executing such stored instructions. Alternatively, or in addition, the UE 106 may include a programmable hardware element such as an FPGA (field-programmable gate array) that is configured to perform any of the method embodiments described herein, or any portion of any of the method embodiments described herein.

The UE 106 may include one or more antennas for communicating using one or more wireless communication protocols or technologies. In some embodiments, the UE 106 may be configured to communicate using, for example, CDMA2000 (1xRTT /1xEV-DO /HRPD /eHRPD) , LTE/LTE-Advanced, or 5G NR using a single shared radio and/or GSM, LTE, LTE-Advanced, or 5G NR using the single shared radio. The shared radio may couple to a single antenna, or may couple to multiple antennas (e.g., for MIMO) for performing wireless communications. In general, a radio may include any combination of a baseband processor, analog RF signal processing circuitry (e.g., including filters, mixers, oscillators, amplifiers, etc. ) , or digital processing circuitry (e.g., for digital modulation as well as other digital processing) . Similarly, the radio may implement one or more receive and transmit chains using the aforementioned hardware. For example, the UE 106 may share one or more parts of a receive and/or transmit chain between multiple wireless communication technologies, such as those discussed above.

In some embodiments, the UE 106 may include separate transmit and/or receive chains (e.g., including separate antennas and other radio components) for each wireless communication protocol with which it is configured to communicate. As a further possibility, the UE 106 may include one or more radios which are shared between multiple wireless communication protocols, and one or more radios which are used exclusively by a single wireless communication protocol. For example, the UE 106 might include a shared radio for communicating using either of LTE or 5G NR (or LTE or 1xRTTor LTE or GSM) , and separate radios for communicating using each of Wi-Fi and Bluetooth. Other configurations are also possible.

FIG. 2: Block Diagram of a Base Station (gNB)

FIG. 2 illustrates an example block diagram of a base station 102, according to some embodiments. It is noted that the base station of FIG. 2 is merely one example of a possible base station. As shown, the base station 102 may include processor (s) 204 which may execute program instructions for the base station 102. The processor (s) 204 may also be coupled to memory management unit (MMU) 240, which may be configured to receive addresses from the processor (s) 204 and translate those addresses to locations in memory (e.g., memory 260 and read only memory (ROM) 250) or to other circuits or devices.

The base station 102 may include at least one network port 270. The network port 270 may be configured to couple to a telephone network and provide a plurality of devices, such as UE devices 106, access to the telephone network as described above in Figures 1 and 2.

The network port 270 (or an additional network port) may also or alternatively be configured to couple to a cellular network, e.g., a core network of a cellular service provider. The core network may provide mobility related services and/or other services to a plurality of devices, such as UE devices 106. In some cases, the network port 270 may couple to a telephone network via the core network, and/or the core network may provide a telephone network (e.g., among other UE devices serviced by the cellular service provider) .

In some embodiments, base station 102 may be a next generation base station, e.g., a 5G New Radio (5G NR) base station, or “gNB” . In such embodiments, base station 102 may be connected to a legacy evolved packet core (EPC) network and/or to a NR core (NRC) network. In addition, base station 102 may be considered a 5G NR cell and may include one or more transition and reception points (TRPs) . In addition, a UE capable of operating according to 5G NR may be connected to one or more TRPs within one or more gNBs.

The base station 102 may include at least one antenna 234, and possibly multiple antennas. The at least one antenna 234 may be configured to operate as a wireless transceiver and may be further configured to communicate with UE devices 106 via radio 230. The antenna 234 communicates with the radio 230 via communication chain 232. Communication chain 232 may be a receive chain, a transmit chain or both. The radio 230 may be configured to communicate via various wireless communication standards, including, but not limited to, 5G NR, LTE, LTE-A, GSM, UMTS, CDMA2000, Wi-Fi, etc.

The base station 102 may be configured to communicate wirelessly using multiple wireless communication standards. In some instances, the base station 102 may include multiple radios, which may enable the base station 102 to communicate according to multiple wireless communication technologies. For example, as one possibility, the base station 102 may include an LTE radio for performing communication according to LTE as well as a 5G NR radio for performing communication according to 5G NR. In such a case, the base station 102 may be capable of operating as both an LTE base station and a 5G NR base station. As another possibility, the base station 102 may include a multi-mode radio which is capable of performing communications according to any of multiple wireless communication technologies (e.g., 5G NR and Wi-Fi, LTE and Wi-Fi, LTE and UMTS, LTE and CDMA2000, UMTS and GSM, etc. ) .

As described further subsequently herein, the base station 102 may include hardware and software components for implementing or supporting implementation of features described herein. The processor 204 of the base station 102 may be configured to implement or support implementation of part or all of the methods described herein, e.g., by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium) . Alternatively, the processor 204 may be configured as a programmable hardware element, such as an FPGA (Field Programmable Gate Array) , or as an ASIC (Application Specific Integrated Circuit) , or a combination thereof. Alternatively (or in addition) the processor 204 of the base station 102, in conjunction with one or more of the other components 230, 232, 234, 240, 250, 260, 270 may be configured to implement or support implementation of part or all of the features described herein.

In addition, as described herein, processor (s) 204 may be comprised of one or more processing elements. In other words, one or more processing elements may be included in processor (s) 204. Thus, processor (s) 204 may include one or more integrated circuits (ICs) that are configured to perform the functions of processor (s) 204. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of processor (s) 204.

Further, as described herein, radio 230 may be comprised of one or more processing elements. In other words, one or more processing elements may be included in radio 230. Thus, radio 230 may include one or more integrated circuits (ICs) that are configured to perform the functions of radio 230. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of radio 230.

In some embodiments, the base station or gNB 102, and/or processors 204 thereof, can be capable of and configured decode, at the base station, a measurement report received from the UE using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report; encode, at the base station, a RRC reconfiguration message for transmission to the UE, wherein the RRC reconfiguration message includes an LTM candidate cell configuration list; decode, at the base station, an RRC reconfiguration complete message received from the UE, to enable the UE to determine an enhancement to the LTM based on an inference output from the AI model at the UE; and execute a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.

FIG. 3: Block Diagram of a Server

FIG. 3 illustrates an example block diagram of a server 104, according to some embodiments. It is noted that the server of FIG. 3 is merely one example of a possible server. As shown, the server 104 may include processor (s) 344 which may execute program instructions for the server 104. The processor (s) 344 may also be coupled to memory management unit (MMU) 374, which may be configured to receive addresses from the processor (s) 344 and translate those addresses to locations in memory (e.g., memory 364 and read only memory (ROM) 354) or to other circuits or devices.

The server 104 may be configured to provide a plurality of devices, such as base station 102, and UE devices 106 access to network functions, e.g., as further described herein.

In some embodiments, the server 104 may be part of a radio access network, such as a 5G New Radio (5G NR) radio access network. In some embodiments, the server 104 may be connected to a legacy evolved packet core (EPC) network and/or to a NR core (NRC) network.

As described herein, the server 104 may include hardware and software components for implementing or supporting implementation of features described herein. The processor 344 of the server 104 may be configured to implement or support implementation of part or all of the methods described herein, e.g., by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium) . Alternatively, the processor 344 may be configured as a programmable hardware element, such as an FPGA (Field Programmable Gate Array) , or as an ASIC (Application Specific Integrated Circuit) , or a combination thereof. Alternatively (or in addition) the processor 344 of the server 104, in conjunction with one or more of the other components 354, 364, and/or 374 may be configured to implement or support implementation of part or all of the features described herein.

In addition, as described herein, processor (s) 344 may be comprised of one or more processing elements. In other words, one or more processing elements may be included in processor (s) 344. Thus, processor (s) 344 may include one or more integrated circuits (ICs) that are configured to perform the functions of processor (s) 344. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of processor (s) 344.

FIG. 4: Block Diagram of a User Equipment (UE)

FIG. 4 illustrates an example simplified block diagram of a communication device 106, according to some embodiments. It is noted that the block diagram of the communication device of FIG. 4 is only one example of a possible communication device. According to embodiments, communication device 106 may be a user equipment (UE) device, a mobile device or mobile station, a wireless device or wireless station, a desktop computer or computing device, a mobile computing device (e.g., a laptop, notebook, or portable computing device) , a tablet, an unmanned aerial vehicle (UAV) , a UAV controller (UAC) and/or a combination of devices, among other devices. As shown, the communication device 106 may include a set of components 400 configured to perform core functions. For example, this set of components may be implemented as a system on chip (SOC) , which may include portions for various purposes. Alternatively, this set of components 400 may be implemented as separate components or groups of components for the various purposes. The set of components 400 may be coupled (e.g., communicatively; directly or indirectly) to various other circuits of the communication device 106.

For example, the communication device 106 may include various types of memory (e.g., including NAND flash 410) , an input/output interface such as connector I/F 420 (e.g., for connecting to a computer system; dock; charging station; input devices, such as a microphone, camera, keyboard; output devices, such as speakers; etc. ) , the display 460, which may be integrated with or external to the communication device 106, and cellular communication circuitry 430 such as for 5G NR, LTE, GSM, etc., and short to medium range wireless communication circuitry 429 (e.g., Bluetooth^TM and WLAN circuitry) . In some embodiments, communication device 106 may include wired communication circuitry (not shown) , such as a network interface card, e.g., for Ethernet.

The cellular communication circuitry 430 may couple (e.g., communicatively; directly or indirectly) to one or more antennas, such as antennas 435 and 436 as shown. The short to medium range wireless communication circuitry 429 may also couple (e.g., communicatively; directly or indirectly) to one or more antennas, such as antennas 437 and 438 as shown. Alternatively, the short to medium range wireless communication circuitry 429 may couple (e.g., communicatively; directly or indirectly) to the antennas 435 and 436 in addition to, or instead of, coupling (e.g., communicatively; directly or indirectly) to the antennas 437 and 438. The short to medium range wireless communication circuitry 429 and/or cellular communication circuitry 430 may include multiple receive chains and/or multiple transmit chains for receiving and/or transmitting multiple spatial streams, such as in a multiple-input multiple output (MIMO) configuration.

In some embodiments, as further described below, cellular communication circuitry 430 may include dedicated receive chains (including and/or coupled to, e.g., communicatively; directly or indirectly. dedicated processors and/or radios) for multiple RATs (e.g., a first receive chain for LTE and a second receive chain for 5G NR) . In addition, in some embodiments, cellular communication circuitry 430 may include a single transmit chain that may be switched between radios dedicated to specific RATs. For example, a first radio may be dedicated to a first RAT, e.g., LTE, and may be in communication with a dedicated receive chain and a transmit chain shared with an additional radio, e.g., a second radio that may be dedicated to a second RAT, e.g., 5G NR, and may be in communication with a dedicated receive chain and the shared transmit chain.

The communication device 106 may also include and/or be configured for use with one or more user interface elements. The user interface elements may include any of various elements, such as display 460 (which may be a touchscreen display) , a keyboard (which may be a discrete keyboard or may be implemented as part of a touchscreen display) , a mouse, a microphone and/or speakers, one or more cameras, one or more buttons, and/or any of various other elements capable of providing information to a user and/or receiving or interpreting user input.

The communication device 106 may further include one or more smart cards 445 that include SIM (Subscriber Identity Module) functionality, such as one or more UICC (s) (Universal Integrated Circuit Card (s) ) cards 445. Note that the term “SIM” or “SIM entity” is intended to include any of various types of SIM implementations or SIM functionality, such as the one or more UICC (s) cards 445, one or more eUICCs, one or more eSIMs, either removable or embedded, etc. In some embodiments, the UE 106 may include at least two SIMs. Each SIM may execute one or more SIM applications and/or otherwise implement SIM functionality. Thus, each SIM may be a single smart card that may be embedded, e.g., may be soldered onto a circuit board in the UE 106, or each SIM 410 may be implemented as a removable smart card. Thus, the SIM (s) may be one or more removable smart cards (such as UICC cards, which are sometimes referred to as “SIM cards” ) , and/or the SIMs 410 may be one or more embedded cards (such as embedded UICCs (eUICCs) , which are sometimes referred to as “eSIMs” or “eSIM cards” ) . In some embodiments (such as when the SIM (s) include an eUICC) , one or more of the SIM (s) may implement embedded SIM (eSIM) functionality; in such an embodiment, a single one of the SIM (s) may execute multiple SIM applications. Each of the SIMs may include components such as a processor and/or a memory; instructions for performing SIM/eSIM functionality may be stored in the memory and executed by the processor. In some embodiments, the UE 106 may include a combination of removable smart cards and fixed/non-removable smart cards (such as one or more eUICC cards that implement eSIM functionality) , as desired. For example, the UE 106 may comprise two embedded SIMs, two removable SIMs, or a combination of one embedded SIMs and one removable SIMs. Various other SIM configurations are also contemplated.

As noted above, in some embodiments, the UE 106 may include two or more SIMs. The inclusion of two or more SIMs in the UE 106 may allow the UE 106 to support two different telephone numbers and may allow the UE 106 to communicate on corresponding two or more respective networks. For example, a first SIM may support a first RAT such as LTE, and a second SIM 410 support a second RAT such as 5G NR. Other implementations and RATs are of course possible. In some embodiments, when the UE 106 comprises two SIMs, the UE 106 may support Dual SIM Dual Active (DSDA) functionality. The DSDA functionality may allow the UE 106 to be simultaneously connected to two networks (and use two different RATs) at the same time, or to simultaneously maintain two connections supported by two different SIMs using the same or different RATs on the same or different networks. The DSDA functionality may also allow the UE 106 to simultaneously receive voice calls or data traffic on either phone number. In certain embodiments the voice call may be a packet switched communication. In other words, the voice call may be received using voice over LTE (VoLTE) technology and/or voice over NR (VoNR) technology. In some embodiments, the UE 106 may support Dual SIM Dual Standby (DSDS) functionality. The DSDS functionality may allow either of the two SIMs in the UE 106 to be on standby waiting for a voice call and/or data connection. In DSDS, when a call/data is established on one SIM, the other SIM is no longer active. In some embodiments, DSDx functionality (either DSDA or DSDS functionality) may be implemented with a single SIM (e.g., a eUICC) that executes multiple SIM applications for different carriers and/or RATs.

As shown, the SOC 400 may include processor (s) 402, which may execute program instructions for the communication device 106 and display circuitry 404, which may perform graphics processing and provide display signals to the display 460. The processor (s) 402 may also be coupled to memory management unit (MMU) 440, which may be configured to receive addresses from the processor (s) 402 and translate those addresses to locations in memory (e.g., memory 406, read only memory (ROM) 450, NAND flash memory 410) and/or to other circuits or devices, such as the display circuitry 404, short to medium range wireless communication circuitry 429, cellular communication circuitry 430, connector I/F 420, and/or display 460. The MMU 440 may be configured to perform memory protection and page table translation or set up. In some embodiments, the MMU 440 may be included as a portion of the processor (s) 402.

As described herein, the communication device 106 may include hardware and software components for implementing the above features for a communication device 106 to communicate a scheduling profile for power savings to a network. The processor 402 of the communication device 106 may be configured to implement part or all of the features described herein, e.g., by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium) . Alternatively (or in addition) , processor 402 may be configured as a programmable hardware element, such as an FPGA (Field Programmable Gate Array) , or as an ASIC (Application Specific Integrated Circuit) . Alternatively (or in addition) the processor 402 of the communication device 106, in conjunction with one or more of the other components 400, 404, 406, 410, 420, 429, 430, 440, 445, 450, 460 may be configured to implement part or all of the features described herein.

In addition, as described herein, processor 402 may include one or more processing elements. Thus, processor 402 may include one or more integrated circuits (ICs) that are configured to perform the functions of processor 402. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of processor (s) 402.

Further, as described herein, cellular communication circuitry 430 and short to medium range wireless communication circuitry 429 may each include one or more processing elements. In other words, one or more processing elements may be included in cellular communication circuitry 430 and, similarly, one or more processing elements may be included in short to medium range wireless communication circuitry 429. Thus, cellular communication circuitry 430 may include one or more integrated circuits (ICs) that are configured to perform the functions of cellular communication circuitry 430. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of cellular communication circuitry 430. Similarly, the short to medium range wireless communication circuitry 429 may include one or more ICs that are configured to perform the functions of short to medium range wireless communication circuitry 429. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of short to medium range wireless communication circuitry 429.

In some embodiments, the UE 106 and/or the processors 402 thereof can be configured to and/or capable of determining, at the UE 106, an enhancement to the LTM based on an inference output from an AI model at the UE;and executing a cell switch at the UE 106 to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.

FIG. 5: Block Diagram of Cellular Communication Circuitry

FIG. 5 illustrates an example simplified block diagram of cellular communication circuitry, according to some embodiments. It is noted that the block diagram of the cellular communication circuitry of FIG. 5 is only one example of a possible cellular communication circuit. According to embodiments, cellular communication circuitry 530, which may be cellular communication circuitry 430, may be included in a communication device, such as communication device 106 described above. As noted above, communication device 106 may be a user equipment (UE) device, a mobile device or mobile station, a wireless device or wireless station, a desktop computer or computing device, a mobile computing device (e.g., a laptop, notebook, or portable computing device) , a tablet and/or a combination of devices, among other devices.

The cellular communication circuitry 530 may couple (e.g., communicatively; directly or indirectly) to one or more antennas, such as antennas 435a-b and 436 as shown (in FIG. 4) . In some embodiments, cellular communication circuitry 530 may include dedicated receive chains (including and/or coupled to, e.g., communicatively; directly or indirectly. dedicated processors and/or radios) for multiple RATs (e.g., a first receive chain for LTE and a second receive chain for 5G NR) . For example, as shown in FIG. 5, cellular communication circuitry 530 may include a modem 510 and a modem 520. Modem 510 may be configured for communications according to a first RAT, e.g., such as LTE or LTE-A, and modem 520 may be configured for communications according to a second RAT, e.g., such as 5G NR.

As shown, modem 510 may include one or more processors 512 and a memory 516 in communication with processors 512. Modem 510 may be in communication with a radio frequency (RF) front end 535. RF front end 535 may include circuitry for transmitting and receiving radio signals. For example, RF front end 535 may include receive circuitry (RX) 532 and transmit circuitry (TX) 534. In some embodiments, receive circuitry 532 may be in communication with downlink (DL) front end 550, which may include circuitry for receiving radio signals via antenna 335a.

Similarly, modem 520 may include one or more processors 522 and a memory 526 in communication with processors 522. Modem 520 may be in communication with an RF front end 540. RF front end 540 may include circuitry for transmitting and receiving radio signals. For example, RF front end 540 may include receive circuitry 542 and transmit circuitry 544. In some embodiments, receive circuitry 542 may be in communication with DL front end 560, which may include circuitry for receiving radio signals via antenna 335b.

In some embodiments, a switch 570 may couple transmit circuitry 534 to uplink (UL) front end 572. In addition, switch 570 may couple transmit circuitry 544 to UL front end 572. UL front end 572 may include circuitry for transmitting radio signals via antenna 336. Thus, when cellular communication circuitry 530 receives instructions to transmit according to the first RAT (e.g., as supported via modem 510) , switch 570 may be switched to a first state that allows modem 510 to transmit signals according to the first RAT (e.g., via a transmit chain that includes transmit circuitry 534 and UL front end 572) . Similarly, when cellular communication circuitry 530 receives instructions to transmit according to the second RAT (e.g., as supported via modem 520) , switch 570 may be switched to a second state that allows modem 520 to transmit signals according to the second RAT (e.g., via a transmit chain that includes transmit circuitry 544 and UL front end 572) .

As described herein, the modem 510 may include hardware and software components for implementing the above features or for time division multiplexing UL data for NSA NR operations, as well as the various other techniques described herein. The processors 512 may be configured to implement part or all of the features described herein, e.g., by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium) . Alternatively (or in addition) , processor 512 may be configured as a programmable hardware element, such as an FPGA (Field Programmable Gate Array) , or as an ASIC (Application Specific Integrated Circuit) . Alternatively (or in addition) the processor 512, in conjunction with one or more of the other components 530, 532, 534, 535, 550, 570, 572, 335a, 335b, and 336 may be configured to implement part or all of the features described herein.

In addition, as described herein, processors 512 may include one or more processing elements. Thus, processors 512 may include one or more integrated circuits (ICs) that are configured to perform the functions of processors 512. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of processors 512.

The processors 522 may be configured to implement part or all of the features described herein, e.g., by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium) . Alternatively (or in addition) , processor 522 may be configured as a programmable hardware element, such as an FPGA (Field Programmable Gate Array) , or as an ASIC (Application Specific Integrated Circuit) . Alternatively (or in addition) the processor 522, in conjunction with one or more of the other components 540, 542, 544, 550, 570, 572, 335a, 335b, and 336 may be configured to implement part or all of the features described herein.

In addition, as described herein, processors 522 may include one or more processing elements. Thus, processors 522 may include one or more integrated circuits (ICs) that are configured to perform the functions of processors 522. In addition, each integrated circuit may include circuitry (e.g., first circuitry, second circuitry, etc. ) configured to perform the functions of processors 522.

FIG. 6: Block Diagram of a Baseband Processor Architecture for a UE

FIG. 6 illustrates example components of a device 600 in accordance with some embodiments. It is noted that the device of FIG. 6 is merely one example of a possible system, and that features of this disclosure may be implemented in any of various UEs, as desired.

In some embodiments, the device 600 may include application circuitry 602, baseband circuitry 604, Radio Frequency (RF) circuitry 606, front-end module (FEM) circuitry 608, one or more antennas 610, and power management circuitry (PMC) 612 coupled together at least as shown. The components of the illustrated device 600 may be included in a UE 106 or a RAN node 102A. In some embodiments, the device 600 may include less elements (e.g., a RAN node may not utilize application circuitry 602, and instead include a processor/controller to process IP data received from an EPC) . In some embodiments, the device 600 may include additional elements such as, for example, memory/storage, display, camera, sensor, or input/output (I/O) interface. In other embodiments, the components described below may be included in more than one device (e.g., said circuitries may be separately included in more than one device for Cloud-RAN (C-RAN) implementations) .

The application circuitry 602 may include one or more application processors. For example, the application circuitry 602 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The processor (s) may include any combination of general-purpose processors and dedicated processors (e.g., graphics processors, application processors, etc. ) . The processors may be coupled with or may include memory/storage and may be configured to execute instructions stored in the memory/storage to enable various applications or operating systems to run on the device 600. In some embodiments, processors of application circuitry 602 may process IP data packets received from an EPC.

The baseband circuitry 604 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The baseband circuitry 604 may include one or more baseband processors or control logic to process baseband signals received from a receive signal path of the RF circuitry 606 and to generate baseband signals for a transmit signal path of the RF circuitry 606. Baseband processing circuity 604 may interface with the application circuitry 602 for generation and processing of the baseband signals and for controlling operations of the RF circuitry 606. For example, in some embodiments, the baseband circuitry 604 may include a third generation (3G) baseband processor 604A, a fourth generation (4G) baseband processor 604B, a fifth generation (5G) baseband processor 604C, or other baseband processor (s) 604D for other existing generations, generations in development or to be developed in the future (e.g., second generation (2G) , sixth generation (6G) , etc. ) . The baseband circuitry 604 (e.g., one or more of baseband processors 604A-D) may handle various radio control functions that enable communication with one or more radio networks via the RF circuitry 606. In other embodiments, some or all of the functionality of baseband processors 604A-D may be included in modules stored in the memory 604G and executed via a Central Processing Unit (CPU) 604E. The radio control functions may include, but are not limited to, signal modulation/demodulation, encoding/decoding, radio frequency shifting, etc. In some embodiments, modulation/demodulation circuitry of the baseband circuitry 604 may include Fast-Fourier Transform (FFT) , precoding, or constellation mapping/demapping functionality. In some embodiments, encoding/decoding circuitry of the baseband circuitry 604 may include convolution, tail-biting convolution, turbo, Viterbi, or Low Density Parity Check (LDPC) encoder/decoder functionality. Embodiments of modulation/demodulation and encoder/decoder functionality are not limited to these examples and may include other suitable functionality in other embodiments.

In some embodiments, the baseband circuitry 604 may include one or more audio digital signal processor (s) (DSP) 604F. The audio DSP (s) 604F may be include elements for compression/decompression and echo cancellation and may include other suitable processing elements in other embodiments. Components of the baseband circuitry may be suitably combined in a single chip, a single chipset, or disposed on a same circuit board in some embodiments. In some embodiments, some or all of the constituent components of the baseband circuitry 604 and the application circuitry 602 may be implemented together such as, for example, on a system on a chip (SOC) .

In some embodiments, the baseband circuitry 604 may provide for communication compatible with one or more radio technologies. For example, in some embodiments, the baseband circuitry 604 may support communication with an evolved universal terrestrial radio access network (EUTRAN) or other wireless metropolitan area networks (WMAN) , a wireless local area network (WLAN) , a wireless personal area network (WPAN) . Embodiments in which the baseband circuitry 604 is configured to support radio communications of more than one wireless protocol may be referred to as multi-mode baseband circuitry.

RF circuitry 606 may enable communication with wireless networks using modulated electromagnetic radiation through a non-solid medium. In various embodiments, the RF circuitry 606 may include switches, filters, amplifiers, etc. to facilitate the communication with the wireless network. RF circuitry 606 may include a receive signal path which may include circuitry to down-convert RF signals received from the FEM circuitry 608 and provide baseband signals to the baseband circuitry 604. RF circuitry 606 may also include a transmit signal path which may include circuitry to up-convert baseband signals provided by the baseband circuitry 604 and provide RF output signals to the FEM circuitry 608 for transmission.

In some embodiments, the receive signal path of the RF circuitry 606 may include mixer circuitry 606a, amplifier circuitry 606b and filter circuitry 606c. In some embodiments, the transmit signal path of the RF circuitry 606 may include filter circuitry 606c and mixer circuitry 606a. RF circuitry 606 may also include synthesizer circuitry 606d for synthesizing a frequency for use by the mixer circuitry 606a of the receive signal path and the transmit signal path. In some embodiments, the mixer circuitry 606a of the receive signal path may be configured to down-convert RF signals received from the FEM circuitry 608 based on the synthesized frequency provided by synthesizer circuitry 606d. The amplifier circuitry 606b may be configured to amplify the down-converted signals and the filter circuitry 606c may be a low-pass filter (LPF) or band-pass filter (BPF) configured to remove unwanted signals from the down-converted signals to generate output baseband signals. Output baseband signals may be provided to the baseband circuitry 604 for further processing. In some embodiments, the output baseband signals may be zero-frequency baseband signals, although this is not a necessity. In some embodiments, mixer circuitry 606a of the receive signal path may comprise passive mixers, although the scope of the embodiments is not limited in this respect.

In some embodiments, the mixer circuitry 606a of the transmit signal path may be configured to up-convert input baseband signals based on the synthesized frequency provided by the synthesizer circuitry 606d to generate RF output signals for the FEM circuitry 608. The baseband signals may be provided by the baseband circuitry 604 and may be filtered by filter circuitry 606c.

In some embodiments, the mixer circuitry 606a of the receive signal path and the mixer circuitry 606a of the transmit signal path may include two or more mixers and may be arranged for quadrature downconversion and upconversion, respectively. In some embodiments, the mixer circuitry 606a of the receive signal path and the mixer circuitry 606a of the transmit signal path may include two or more mixers and may be arranged for image rejection (e.g., Hartley image rejection) . In some embodiments, the mixer circuitry 606a of the receive signal path and the mixer circuitry 606a may be arranged for direct downconversion and direct upconversion, respectively. In some embodiments, the mixer circuitry 606a of the receive signal path and the mixer circuitry 606a of the transmit signal path may be configured for super-heterodyne operation.

In some embodiments, the output baseband signals and the input baseband signals may be analog baseband signals, although the scope of the embodiments is not limited in this respect. In some alternate embodiments, the output baseband signals and the input baseband signals may be digital baseband signals. In these alternate embodiments, the RF circuitry 606 may include analog-to-digital converter (ADC) and digital-to-analog converter (DAC) circuitry and the baseband circuitry 604 may include a digital baseband interface to communicate with the RF circuitry 606.

In some dual-mode embodiments, a separate radio IC circuitry may be provided for processing signals for each spectrum, although the scope of the embodiments is not limited in this respect.

In some embodiments, the synthesizer circuitry 606d may be a fractional-N synthesizer or a fractional N/N+1 synthesizer, although the scope of the embodiments is not limited in this respect as other types of frequency synthesizers may be suitable. For example, synthesizer circuitry 606d may be a delta-sigma synthesizer, a frequency multiplier, or a synthesizer comprising a phase-locked loop with a frequency divider.

The synthesizer circuitry 606d may be configured to synthesize an output frequency for use by the mixer circuitry 606a of the RF circuitry 606 based on a frequency input and a divider control input. In some embodiments, the synthesizer circuitry 606d may be a fractional N/N+1 synthesizer.

In some embodiments, frequency input may be provided by a voltage controlled oscillator (VCO) , although that is not a necessity. Divider control input may be provided by either the baseband circuitry 604 or the applications processor 602 depending on the desired output frequency. In some embodiments, a divider control input (e.g., N) may be determined from a look-up table based on a channel indicated by the applications processor 602.

Synthesizer circuitry 606d of the RF circuitry 606 may include a divider, a delay-locked loop (DLL) , a multiplexer and a phase accumulator. In some embodiments, the divider may be a dual modulus divider (DMD) and the phase accumulator may be a digital phase accumulator (DPA) . In some embodiments, the DMD may be configured to divide the input signal by either N or N+1 (e.g., based on a carry out) to provide a fractional division ratio. In some example embodiments, the DLL may include a set of cascaded, tunable, delay elements, a phase detector, a charge pump and a D-type flip-flop. In these embodiments, the delay elements may be configured to break a VCO period up into Nd equal packets of phase, where Nd is the number of delay elements in the delay line. In this way, the DLL provides negative feedback to help ensure that the total delay through the delay line is one VCO cycle.

In some embodiments, synthesizer circuitry 606d may be configured to generate a carrier frequency as the output frequency, while in other embodiments, the output frequency may be a multiple of the carrier frequency (e.g., twice the carrier frequency, four times the carrier frequency) and used in conjunction with quadrature generator and divider circuitry to generate multiple signals at the carrier frequency with multiple different phases with respect to each other. In some embodiments, the output frequency may be a LO frequency (fLO) . In some embodiments, the RF circuitry 606 may include an IQ/polar converter.

FEM circuitry 608 may include a receive signal path which may include circuitry configured to operate on RF signals received from one or more antennas 610, amplify the received signals and provide the amplified versions of the received signals to the RF circuitry 606 for further processing. FEM circuitry 608 may also include a transmit signal path which may include circuitry configured to amplify signals for transmission provided by the RF circuitry 606 for transmission by one or more of the one or more antennas 610. In various embodiments, the amplification through the transmit or receive signal paths may be done solely in the RF circuitry 606, solely in the FEM 608, or in both the RF circuitry 606 and the FEM 608.

In some embodiments, the FEM circuitry 608 may include a TX/RX switch to switch between transmit mode and receive mode operation. The FEM circuitry may include a receive signal path and a transmit signal path. The receive signal path of the FEM circuitry may include an LNA to amplify received RF signals and provide the amplified received RF signals as an output (e.g., to the RF circuitry 606) . The transmit signal path of the FEM circuitry 608 may include a power amplifier (PA) to amplify input RF signals (e.g., provided by RF circuitry 606) , and one or more filters to generate RF signals for subsequent transmission (e.g., by one or more of the one or more antennas 610) .

In some embodiments, the PMC 612 may manage power provided to the baseband circuitry 604. In particular, the PMC 612 may control power-source selection, voltage scaling, battery charging, or DC-to-DC conversion. The PMC 612 may often be included when the device 600 is capable of being powered by a battery, for example, when the device is included in a UE. The PMC 612 may increase the power conversion efficiency while providing desirable implementation size and heat dissipation characteristics.

While FIG. 6 shows the PMC 612 coupled only with the baseband circuitry 604, in other embodiments the PMC 612 may be additionally or alternatively coupled with, and perform similar power management operations for, other components such as, but not limited to, application circuitry 602, RF circuitry 606, or FEM 608.

In some embodiments, the PMC 612 may control, or otherwise be part of, various power saving mechanisms of the device 600. For example, if the device 600 is in a radio resource control_Connected (RRC_Connected) state, where it is still connected to the RAN node as it expects to receive traffic shortly, then it may enter a state known as Discontinuous Reception Mode (DRX) after a period of inactivity. During this state, the device 600 may power down for brief intervals of time and thus save power.

If there is no data traffic activity for an extended period of time, then the device 600 may transition off to an RRC_Idle state, where it disconnects from the network and does not perform operations such as channel quality feedback, handover, etc. The device 600 goes into a very low power state and it performs paging where, again, it periodically wakes up to listen to the network and then powers down at least portions of the device again. The device 600 may not receive data in this state. In order to receive data, it will transition back to an RRC_Connected state.

An additional power saving mode may allow a device to be unavailable to the network for periods longer than a paging interval (ranging from seconds to a few hours) . During this time, the device is totally unreachable to the network and may power down completely. Any data sent during this time incurs a large delay and it is assumed the delay is acceptable.

Processors of the application circuitry 602 and processors of the baseband circuitry 604 may be used to execute elements of one or more instances of a protocol stack. For example, processors of the baseband circuitry 604, alone or in combination, may be used for encoding measurement reports for transmission from the UE 106 to the base station 102 and decoding RRC reconfiguration messages received at the UE from the base station. These examples are not intended to be limiting. The baseband circuitry can be used as previously described.

FIG. 7: Block Diagram of an Interface of Baseband Circuitry

FIG. 7 illustrates example interfaces of baseband circuitry in accordance with some embodiments. It is noted that the baseband circuitry of FIG. 7 is merely one example of a possible circuitry, and that features of this disclosure may be implemented in any of various systems, as desired.

As discussed above, the baseband circuitry 604 of FIG. 6 may comprise processors 604A-604E and a memory 604G utilized by said processors. Each of the processors 604A-604E may include a memory interface, 704A-704E, respectively, to send/receive data to/from the memory 604G.

The baseband circuitry 604 may further include one or more interfaces to communicatively couple to other circuitries/devices, such as a memory interface 712 (e.g., an interface to send/receive data to/from memory external to the baseband circuitry 604) , an application circuitry interface 714 (e.g., an interface to send/receive data to/from the application circuitry 602 of FIG. 6) , an RF circuitry interface 716 (e.g., an interface to send/receive data to/from RF circuitry 606 of FIG. 6) , a wireless hardware connectivity interface 718 (e.g., an interface to send/receive data to/from Near Field Communication (NFC) components, components (e.g., Low Energy) , components, and other communication components) , and a power management interface 720 (e.g., an interface to send/receive power or control signals to/from the PMC 612.

FIG. 8: Control Plane Protocol Stack

FIG. 8 is an illustration of a control plane protocol stack in accordance with some embodiments. In this embodiment, a control plane 800 is shown as a communications protocol stack between the UE 106a (or alternatively, the UE 106b) , the RAN node 102A (or alternatively, the RAN node 102B) , and the mobility management entity (MME) 621.

The PHY layer 801 may transmit or receive information used by the MAC layer 802 over one or more air interfaces. The PHY layer 801 may further perform link adaptation or adaptive modulation and coding (AMC) , power control, cell search (e.g., for initial synchronization and handover purposes) , and other measurements used by higher layers, such as the RRC layer 805. The PHY layer 801 may still further perform error detection on the transport channels, forward error correction (FEC) coding/decoding of the transport channels, modulation/demodulation of physical channels, interleaving, rate matching, mapping onto physical channels, and Multiple Input Multiple Output (MIMO) antenna processing.

The MAC layer 802 may perform mapping between logical channels and transport channels, multiplexing of MAC service data units (SDUs) from one or more logical channels onto transport blocks (TB) to be delivered to PHY via transport channels, de-multiplexing MAC SDUs to one or more logical channels from transport blocks (TB) delivered from the PHY via transport channels, multiplexing MAC SDUs onto TBs, scheduling information reporting, error correction through hybrid automatic repeat request (HARQ) , and logical channel prioritization.

The RLC layer 803 may operate in a plurality of modes of operation, including: Transparent Mode (TM) , Unacknowledged Mode (UM) , and Acknowledged Mode (AM) . The RLC layer 803 may execute transfer of upper layer protocol data units (PDUs) , error correction through automatic repeat request (ARQ) for AM data transfers, and concatenation, segmentation and reassembly of RLC SDUs for UM and AM data transfers. The RLC layer 803 may also execute re-segmentation of RLC data PDUs for AM data transfers, reorder RLC data PDUs for UM and AM data transfers, detect duplicate data for UM and AM data transfers, discard RLC SDUs for UM and AM data transfers, detect protocol errors for AM data transfers, and perform RLC re-establishment.

The Packet Data Convergence Protocol (PDCP) layer 804 may execute header compression and decompression of IP data, maintain PDCP Sequence Numbers (SNs) , perform in-sequence delivery of upper layer PDUs at re-establishment of lower layers, eliminate duplicates of lower layer SDUs at re-establishment of lower layers for radio bearers mapped on RLC AM, cipher and decipher control plane data, perform integrity protection and integrity verification of control plane data, control timer-based discard of data, and perform security operations (e.g., ciphering, deciphering, integrity protection, integrity verification, etc. ) .

The main services and functions of the RRC layer 805 may include broadcast of system information (e.g., included in Master Information Blocks (MIBs) or System Information Blocks (SIBs) related to the non-access stratum (NAS) ) , broadcast of system information related to the access stratum (AS) , paging, establishment, maintenance and release of an RRC connection between the UE and E-UTRAN (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release) , establishment, configuration, maintenance and release of point to point Radio Bearers, security functions including key management, inter radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting. Said MIBs and SIBs may comprise one or more information elements (IEs) , which may each comprise individual data fields or data structures.

The UE 601 and the RAN node 102A may utilize a Uu interface (e.g., an LTE-Uu interface) to exchange control plane data via a protocol stack comprising the PHY layer 801, the MAC layer 802, the RLC layer 803, the PDCP layer 804, and the RRC layer 805.

The non-access stratum (NAS) protocols 806 form the highest stratum of the control plane between the UE 601 and the MME 621. The NAS protocols 806 support the mobility of the UE 601 and the session management procedures to establish and maintain IP connectivity between the UE 601 and the P-GW 623.

The S1 Application Protocol (S1-AP) layer 815 may support the functions of the S1 interface and comprise Elementary Procedures (EPs) . An EP is a unit of interaction between the RAN node 102A and the network 100. The S1-AP layer services may comprise two groups: UE-associated services and non UE-associated services. These services perform functions including, but not limited to: E-UTRAN Radio Access Bearer (E-RAB) management, UE capability indication, mobility, NAS signaling transport, RAN Information Management (RIM) , and configuration transfer.

The Stream Control Transmission Protocol (SCTP) layer (alternatively referred to as the SCTP/IP layer) 814 may ensure reliable delivery of signaling messages between the RAN node 102A and the MME 621 based, in part, on the IP protocol, supported by the IP layer 813. The L2 layer 812 and the L1 layer 811 may refer to communication links (e.g., wired or wireless) used by the RAN node and the MME to exchange information.

The RAN node 102A and the MME 621 may utilize an S1-MME interface to exchange control plane data via a protocol stack comprising the L1 layer 811, the L2 layer 812, the IP layer 813, the SCTP layer 814, and the S1-AP layer 815.

FIG. 9: User Plane Protocol Stack

FIG. 9 is an illustration of an example of a user plane protocol stack in accordance with some embodiments. In this embodiment, a user plane 900 is shown as a communications protocol stack between the UE 106A (or alternatively, the UE 106B or 106N) , the RAN node 102A (or alternatively, the RAN node 102B) , the S-GW 622, and the P-GW 623. The user plane 900 may utilize at least some of the same protocol layers as the control plane 800. For example, the UE 601 and the RAN node 102A may utilize a Uu interface (e.g., an LTE-Uu interface) to exchange user plane data via a protocol stack comprising the PHY layer 801, the MAC layer 802, the RLC layer 803, the PDCP layer 804.

The General Packet Radio Service (GPRS) Tunneling Protocol for the user plane (GTP-U) layer 904 may be used for carrying user data within the GPRS core network and between the radio access network and the core network. The user data transported can be packets in any of IPv4, IPv6, or PPP formats, for example. The UDP and IP security (UDP/IP) layer 903 may provide checksums for data integrity, port numbers for addressing different functions at the source and destination, and encryption and authentication on the selected data flows. The RAN node 102A and the S-GW 622 may utilize an S1-U interface to exchange user plane data via a protocol stack comprising the L1 layer 811, the L2 layer 812, the UDP/IP layer 903, and the GTP-U layer 904. The S-GW 622 and the P-GW 623 may utilize an S5/S8a interface to exchange user plane data via a protocol stack comprising the L1 layer 811, the L2 layer 812, the UDP/IP layer 903, and the GTP-U layer 904. As discussed above with respect to FIG. 8, NAS protocols support the mobility of the UE 106 and the session management procedures to establish and maintain IP 813 connectivity between the UE 106 and the P-GW 623.

For the remainder of this disclosure, references to base station (gNB) and user equipment (UE) are assumed to refer to base station (gNB) 102 and user equipment (UE) 106, respectively, even though specific reference numerals may be omitted.

FIG. 10: Core Network

FIG. 10 illustrates an example architecture of a system 1000 including a core network (CN) 1020 in accordance with various embodiments. The CN 1020 may be a core network for a 5G System (which may be referred to as a 5GC) . The system 1000 is shown to include a UE 1001, which may be the same or similar to the UEs 106A, 106B, or 106N discussed previously; a (R) AN 102, which may be the same or similar to the BSs 102A or 102N discussed previously; and a data network (DN) 1003, which may be, for example, operator services, Internet access, or 3rd party services; and a CN 1020. The CN 1020 may include a number of network functions including an Authentication Server Function (AUSF) 1022; an Access and Mobility Management Function (AMF) 1021; a Session Management Function (SMF) 1024; a Network Exposure Function (NEF) 1023; a Policy Control Function (PCF) 1026; a Network Repository Function (NRF) 1025; a Unified Data Management (UDM) 1027; an Application Function (AF) 1028; a User Plane Function (UPF) 1002; and a Network Slice Selection Function (NSSF) 1029. These network functions may be implemented, in some cases, as virtualized software based functions/services.

The UPF 1002 may act as an anchor point for intra-RAT and inter-RAT mobility, an external packet data unit (PDU) session point of interconnect to DN 1003, and a branching point to support mufti-homed PDU session. A PDU session is a logical connection between the UE and the DN. The UPF 1002 may also perform packet routing and forwarding, perform packet inspection, enforce the user plane part of policy rules, lawfully intercept packets (user plane (UP) collection) , perform traffic usage reporting, perform quality of service (QoS) handling for a user plane (e.g., packet filtering, gating, UL/DL rate enforcement) , perform Uplink Traffic verification (e.g., Service Data Flows (SDF) to QoS flow mapping) , transport level packet marking in the uplink and downlink, and perform downlink packet buffering and downlink data notification triggering. UPF 1002 may include an uplink classifier to support routing traffic flows to a data network, The DN 1003 may represent various network operator services, Internet access, or third party services. DN 1003 may include, or be similar to, application server 430 discussed previously. The UPF 1002 may interact with the SMF 1024 via an N4 reference point between the SMF 1021 and the UPF 1002.

The AUSF 1022 may store data for authentication of UE 1001 and handle authentication-related functionality, The AUSF 1022 may facilitate a common authentication frame work for various access types. The AUSF 1022 may communicate with the AMF 1021 via an N12 reference point between the AMF 1021 and the AUSF 1022; and may communicate with the UDM 1027 via an N13 reference point between the UDM 1027 and the AUSF 1022. Additionally, the AUSF 1022 may exhibit an Nausf service-based interface.

The AMF 1021 may be responsible for registration management (e.g., for registering UE 1001, etc. ) , connection management, reachability management, mobility management, and lawful interception of AMF-related events, and access authentication and authorization. The AMF 1021 may be a termination point for the an N11 reference point between the AMF 1021 and the SMF 1024. The AMF 1021 may provide transport for SM messages between the UE 1001 and the SMF 1024, and act as a transparent proxy for routing SM messages. AMF 1021 may also provide transport for Short Message Service (SMS) messages between UE 1001 and an SMSF (not shown by FIG. 10) . AMF 1021 may act as a security anchor function (SEAF) , which may include interaction with the AUSF 1022 and the UE 1001, receipt of an intermediate key that was established as a result of the UE 1001 authentication process. Where Universal Subscriber Identity Module (USIM) based authentication is used, the AMF 1021 may retrieve the security material from the AUSF 1022. AMF 1021 may also include a Security Context Management (SCM) function, which receives a key from the SEAF that it uses to derive access-network specific keys. Furthermore, AMF 1021 may be a termination point of a RAN control plane (CP) interface, which may include or be an N2 reference point between the (R) AN 1010 and the AMF 1021; and the AMF 1021 may be a termination point of NAS (N1) signaling, and perform NAS ciphering and integrity protection.

AMF 1021 may also support NAS signaling with a UE 1001 over a non-3GPP Inter-Working Function (N3IWF) interface. The N3IWF may be used to provide access to untrusted entities. N3IWF may be a termination point for the N2 interface between the (R) AN 1010 and the AMF 1021 for the control plane, and may be a termination point for the N3 reference point between the (R) AN 1010 and the UPF 1002 for the user plane. As such, the AMF 1021 may handle N2 signaling from the SMF 1024 and the AMF 1021 for PDU sessions and encapsulate/de encapsulate packets for IPSec and N3 tunneling, mark N3 user-plane packets in the uplink, and enforce QoS corresponding to N3 packet marking while considering QoS requirements associated with such marking received over N2. N3IWF may also relay uplink and downlink control plane non-access stratum (NAS) signaling between the UE 1001 and AMF 1021 via an N1 reference point between the UE 1001 and the AMF 1021, and relay uplink and downlink user-plane packets between the UE 1001 and UPF 1002. The N3IWF also provides mechanisms for internet protocol security (IPsec) tunnel establishment with the UE 1001. The AMF 1021 may exhibit an Namf service based interface, and may be a termination point for an N14 reference point between two AMFs 1021 and an N17 reference point between the AMF 1021 and a 5G Equipment Identity Register (5G-EIR) (not shown by FIG. 10) .

The UE 1001 may need to register with the AMF 1021 in order to receive network services. Registration Management (RM) is used to register or deregister the UE 1001 with the network (e.g., AMF 1021) , and establish a UE context in the network (e.g., AMF 1021) . The UF 1001 may operate in an RM-REGISTERED state or an RM-DEREGISTERED state. In the RM-DEREGISTERED state, the UE 1001 is not registered with the network, and the UE context in AMF 1021 holds no valid location or routing information for the UE 1001 so the UE 1001 is not reachable by the AMF 1021. In the RM REGISTERED state, the UE 1001 is registered with the network, and the UE context in AMF 1021 may hold a valid location or routing information for the UE 1001 so the UE 1001 is reachable by the AMF 1021. In the RM-REGISTERED state, the UE 1001 may perform mobility registration update procedures, perform periodic registration update procedures triggered by expiration of the periodic update timer (e.g., to notify the network that the UE 1001 is still active) , and perform a Registration Update procedure to update UE capability information or to re-negotiate protocol parameters with the network, among others.

The AMF 1021 may store one or more RM contexts for the UE 1001, where each RM context is associated with a specific access to the network. The RM context may be a data structure, database object, etc. that indicates or stores, inter glia, a registration state per access type and the periodic update timer. The AMF 1021 may also store a 5GC mobility management (MM) context that may be the same or similar to the evolved packet services (EPS) Mobility Management (E) MM context discussed previously. In various embodiments, the AMF 1021 may store a CE mode B Restriction parameter of the UE 1001 in an associated MM context or registration management (RM) context. The AMF 1021 may also derive the value, when needed, from the UE's usage setting parameter already stored in the UE context (and/or MM/RM context) .

Connection Management (CM) may be used to establish and release a signaling connection between the UE 1001 and the AMF 1021 over the N1 interface. The signaling connection is used to enable NAS signaling exchange between the UE 1001 and the CN 1020, and comprises both the signaling connection between the UE and the AN (e.g., RRC connection or UE-N3IWF connection for non-3GPP access) and the N2 connection for the UE 1001 between the AN (e.g., AN 1010) and the AMF 1021. The UE 1001 may operate in one of two CM states, CM-IDLE mode or CM-CONNECTED mode. When the UE 1001 is operating in the CM-IDLE state/mode, the UE 1001 may have no NAS signaling connection established with the AMF 1021 over the N1 interface, and there may be (R) AN 1010 signaling connection (e.g., N2 and/or N3 connections) for the UE 1001. When the UE 1001 is operating in the CM-CONNECTED state/mode, the UE 1001 may have an established NAS signaling connection with the AMF 1021 over the N1 interface, and there may be a (R) AN 1010 signaling connection (e.g., N2 and/or N3 connections) for the UE 1001. Establishment of an N2 connection between the (R) AN 1010 and the AMF 1021 may cause the UE 1001 to transition from CM-IDLE mode to CM-CONNECTED mode, and the UE 1001 may transition from the CM-CONNECTED mode to the CM-IDLE mode when N2 signaling between the (R) AN 1010 and the AMF 1021 is released.

The SMF 1024 may be responsible for session management (SM) session establishment, modify and release, including tunnel maintain between UPF and AN node) ; UE IP address allocation and management (including optional authorization) ; selection and control of UP function; configuring traffic steering at UPF to route traffic to proper destination; termination of interfaces toward policy control functions; controlling part of policy enforcement and QoS; lawful intercept (for SM events and interface to LI system) ; termination of SM parts of NAS messages; downlink data notification; initiating AN specific SM information, sent via AMF over N2 to AN; and determining SSC mode of a session. SM may refer to management of a PDU session, and a PDU session or "session" may refer to a PDU connectivity service that provides or enables the exchange of PDUs between a UE 1001 and a data network (DN) 1003 identified by a Data Network Name (DNN) . PDU sessions may be established upon UE 1001 request, modified upon UE 1001 and CN 1020 request, and released upon UE 1001 and CN 1020 request using NAS SM signaling exchanged over the N1 reference point between the UE 1001 and the SMF 1024. Upon request from an application server, the CN 1020 may trigger a specific application in the UE 1001. In response to receipt of the trigger message, the UE 1001 may pass the trigger message (or relevant parts/information of the trigger message) to one or more identified applications in the UE 1001. The identified application (s) in the UE 1001 may establish a PDU session to a specific data network name (DNN) . The SMF 1024 may check whether the UE 1001 requests are compliant with user subscription information associated with the UE 1001. In this regard, the SMF 1024 may retrieve and/or request to receive update notifications on SMF 1024 level subscription data from the UDM 1027.

The SMF 1024 may include the following roaming functionality: handling local enforcement to apply QoS SLAB virtual Public Land Mobile Network (VPLMN) ; charging data collection and charging interface (VPLMN) ; lawful intercept (in VPLMN for SM events and interface to LI system) ; and support for interaction with external DN for transport of signaling for PDU session authorization/authentication by external DN. An N16 reference point between two SMFs 1024 may be included in the system 1000, which may be between another SMF 1024 in a visited network and the SMF 1024 in the home network in roaming scenarios. Additionally, the SMF 1024 may exhibit the Nsmf service-based interface.

The NEF 1023 may provide means for securely exposing the services and capabilities provided by 3GPP network functions for third party, internal exposure/re-exposure, Application Functions (e.g., AF 1028) , edge computing or fog computing systems, etc. In such embodiments, the NEF 1023 may authenticate, authorize, and/or throttle the AFS. NEF 1023 may also translate information exchanged with the AF 1028 and information exchanged with internal network functions. For example, the NEF 1023 may translate between an AF-Service-Identifier and an internal SCC information. NEF 1023 may also receive information from other network functions (NFs) based on exposed capabilities of other network functions. This information may be stored at the NEF 1023 as structured data, or at a data storage NF using standardized interfaces. The stored information can then be re-exposed by the NEF 1023 to other NFs and AFs, and/or used for other purposes such as analytics. Additionally, the NEF 1023 may exhibit an Nnef service-based interface.

The NRF 1025 may support service discovery functions, receive NF discovery requests from NF instances, and provide the information of the discovered NF instances to the NF instances. NRF 1025 also maintains information of available NF instances and their supported services. As used herein, the terms "instantiate, " "instantiation, " and the like may refer to the creation of an instance, and an "instance" may refer to a concrete occurrence of an object, which may occur, for example, during execution of program code. Additionally, the NRF 1025 may exhibit the Nnrf service based interface.

The PCF 1026 may provide policy rules to control plane function (s) to enforce them, and may also support unified policy framework to govern network behavior, The PCF 1026 may also implement a front end (FE) to access subscription information relevant for policy decisions in a UDR of the UDM 1027. The PCF 1026 may communicate with the AMF 1021 via an N15 reference point between the PCF 1026 and the AMF 1021, which may include a PCF 1026 in a visited network and the AMF 1021 in case of roaming scenarios. The PCF 1026 may communicate with the AF 1028 via an NS reference point between the PCF 1026 and the AF 1028; and with the SMF 1024 via an N7 reference point between the PCF 1026 and the SMF 1024, The system 1000 and/or CN 1020 may also include an N24 reference point between the PCF 1026 (in the home network) and a PCF 1026 in a visited network, Additionally, the PCF 1026 may exhibit an Npcf service-based interface.

The UDM 1027 may handle subscription-related information to support the network entities'handling of communication sessions, and may store subscription data of UE 1001. For example, subscription data may be communicated between the UDM 1027 and the AMF 1021 via an NS reference point between the UDM 1027 and the AMF. The UDM 1027 may include two parts, an application FE and a UDR (the FE and UDR are not shown by FIG. 10) . The UDR may store subscription data and policy data for the UDM 1027 and the PCF 1026, and/or structured data for exposure and application data (including PFDs for application detection, application request information for multiple UEs 1001) for the NEF 1023. The Nadr service-based interface may be exhibited by the UDR 221 to allow the UDM 1027, PCF 1026, and NEF 1023 to access a particular set of the stored data, as well as to read, update (e.g., add, modify) , delete, and subscribe to notification of relevant data changes in the UDR. The UDM may include a UDM-FE, which is in charge of processing credentials, location management, subscription management and so on. Several different front ends may serve the same user in different transactions. The UDM-FE accesses subscription information stored in the UDR and performs authentication credential processing, user identification handling, access authorization, registration/mobility management, and subscription management. The UDR may interact with the SMF 1024 via an Nl0 reference point between the UDM 1027 and the SMF 1024. UDM 1027 may also support SMS management, wherein an SMS-FE implements the similar application logic as discussed previously. Additionally, the UDM 1027 may exhibit the Nudm service based interface.

The AF 1028 may provide application influence on traffic routing, provide access to the NCE, and interact with the policy framework for policy control. The NCE may be a mechanism that allows the CN 1020 and AF 1028 to provide information to each other via NEF 1023, which may be used for edge computing implementations. In such implementations, the network operator and third party services may be hosted close to the UE 1001 access point of attachment to achieve an efficient service delivery through the reduced end-to-end latency and load on the transport network. For edge computing implementations, the 5GC may select a UPF 1002 close to the UE 1001 and execute traffic steering from the UPF 502 to ON 1003 via the N6 interface. This may be based on the UE subscription data, UE location, and information provided by the AF 1028. In this way, the AF 1028 may influence UPF (re) selection and traffic routing. Based on operator deployment, when AF 1028 is considered to be a trusted entity, the network operator may permit AF 1028 to interact directly with relevant NFs. Additionally, the AF 1028 may exhibit an Naf service-based interface.

The NSSF 1029 may select a set of network slice instances serving the UE 501. The NSSF 1029 may also determine allowed Network Slice Selection Assistance Information (NSSAI) and the mapping to the subscribed single NSSAI (S-NSSAI) is, if needed. The NSSF 1029 may also determine the AMF set to be used to serve the UE 1001, or a list of candidate AMF (s) 1021 based on a suitable configuration and possibly by querying the NRF 1025. The selection of a set of network slice instances for the UE 1001 may be triggered by the AMF 1021 with which the UE 1001 is registered by interacting with the NSSF 1029, which may lead to a change of AMF 1021. The NSSF 1029 may interact with the AMF 1021 via an N22 reference point between AMF 1021 and NSSF 1029; and may communicate with another NSSF 1029 in a visited network via an N31 reference point (not shown by FIG. 10) . Additionally, the NSSF 1029 may exhibit an Nnssf service-based interface.

As discussed previously, the CN 1020 may include a short message service function (SMSF) , which may be responsible for SMS subscription checking and verification, and relaying SM messages to/from the UE 1001 to/from other entities, such as an SMS-GMSC/IWMSC/SMS-router. The SMS may also interact with AMF 1021 and UDM 1027 for a notification procedure that the UE 1001 is available for SMS transfer (e.g., set a UE not reachable flag, and notifying UDM 1027 when UE 1001 is available for SMS) .

The CN 1020 may also include other elements that are not shown by FIG. 10, such as a Data Storage system/architecture, a 5G-EIR, a Security Edge Protection Proxy (SEPP) , and the like. The Data Storage system may include a Structured Data Storage Network Function (SDSF) , air Unstructured Data Storage Function (UDSF) , and/or the like. Any network function (NF) may store and retrieve unstructured data into/from the UDSF (e.g., UE contexts) , via N18 reference point between any NF and the UDSF (not shown by FIG. 10) , Individual NFs may share a UDSF for storing their respective unstructured data or individual NFs may each have their own UDSF located at or near the individual NFs. Addition ally, the UDSF may exhibit an Nudsf service-based interface (not shown by FIG. 10) . The 5G-EIR may be an NF that checks the status of permanent equipment identifier (PEI) for determining whether particular equipment/entities are blacklisted from the network; and the SEPP may be a non-transparent proxy that performs topology hiding, message filtering, and policing on inter-PLMN control plane interfaces.

Additionally, there may be many more reference points and/or service-based interfaces between the NF services in the NFs; however, these interfaces and reference points have been omitted from FIG. 10 for clarity. In one example, the CN 1020 may include an Nx interface, which is an inter-CN interface between a mobility management entity (MME) and the AMF 1021 in order to enable interworking between CN 1020 and a CN in a 4G system. Other example interfaces/reference points may include an N5G-EIR service-based interface exhibited by a 5G-EIR, an N27 reference point between the NRF in the visited network and the NRF in the home network; and an N31 reference point between the NSSF in the visited network and the NSSF in the home network.

FIG. 11A: UE Beamforming using Layer 3

The transition from 3GPP LTE to NR provided the promise of significantly increased bandwidth to provide greater download and upload speeds with reduced latency. One technique for accomplishing this is through the use of higher frequency bands. The NR specification is split into two frequency bands, frequency range one (FR1) , covering bands within the frequency range of 410 MHz to 7.125 GHz, and frequency range two (FR2) , covering bands that are greater than 7.125 GHz, including bands with center frequencies from 28 GHz to 60 GHz, and single channel bandwidths from 50 MHz up to 400 MHz, and even 2000 MHz for band n263.

The so called millimeter wave frequencies in FR2 can provide much greater bandwidth and transmission speeds to user equipment relative to the smaller 3GPP bands in FR1. However, the higher frequency ranges in FR2 also result in much greater signal losses caused by absorption of the millimeter wave carrier signals in the atmosphere.

To overcome the significant signal losses in FR2, while still meeting the specific absorption rate (SAR) transmission power limits at the UE within each country, the NR specification has adopted the use of beamforming. By transmitting power in a relatively narrow beam, a signal can propagate over a greater distance to a receiver relative to a transmission using an omnidirectional or wide angle antenna.

FIG. 11A provides an example illustration of a UE 106 communicating with multiple cells using receive beam forming to increase downlink performance, in accordance with some embodiments. As a baseline, layer 3 measurements, such as radio resource monitoring (RRM) requirements, have been derived based on the assumption that the UE 106 can measure with only one beam at a time. When the UE 106 is performing L3 measurements, the UE 106 needs to perform receive beam sweeping so that the UE can detect and measure all of the neighbor cells in different directions.

5G NR has introduced cell measurement by using synchronization signal (SS) /physical broadcast channel (PBCH) Block (SSB) . The SSB is composed of synchronization signals, including a primary synchronization signal and a secondary synchronization signal, and the PBCH. The number of SSB in one burst depends on the frequency band of the signal that is communicated. If the center frequency Fc is less than 3 GHz, the number of SSB is four. When Fc is between 3 GHz and 6 GHz, the number of SSB is 8. For center frequencies greater than 6 GHz, in FR2, the number of SSB is 64 within one burst, thereby enabling signals to be transmitted using beamforming, with multiple potential signals per cell. The SSB periodicity can be configured for each cell, with a range of 5, 10, 20, 40, 80 or 160 ms.

An SSB based RRM measurement timing configuration (SMTC) window provides a time period and a periodicity for a UE to measure the SSB. A UE can receive an SMTC window periodicity and duration from a base station. The UE can then detect and measure the SSBs within the window and report the measurement results back to the base station. When the UE only has a single receive chain, the UE can either communicate with the base station or perform L3 measurements on neighboring cells, but cannot do both simultaneously. The base station can allot a time period, referred to as a measurement gap, during which the UE can perform the L3 measurements of one or more SSBs in neighboring cells. The base station can appropriately set the SMTC window and measurement gap length based on the SSB burst periodicity. Different SMTC periods can be set for a primary measurement of the timing offset and duration for the SSB. A second SMTC window can be used to perform secondary measurement timing for the synchronization signal.

Since the UE can only communicate with one beam at a time, the UE cannot perform any downlink (DL) reception or uplink (UL) transmission with a serving cell when the UE is performing the L3 measurements with neighbor cells. This can be reflected in scheduling restrictions that are specified in 3GPP Technical Specification (TS) 38.133. For example, in section 9.2.5.3.3 of TS 38.133 Ver 18.3.0 (Sept, 2023) , scheduling availability of a UE that is performing measurements on FR2 is discussed. With intra-frequency measurements without a measurement gap, when the UE is performing Layer 3 or Layer 1 measurements, such as synchronization signal (SS) received signal received power (RSRP) , or SS-SINR measurements on an FR2 intra-frequency cell, the UE is not expected to transmit on the physical uplink control channel (PUCCH) , physical uplink shared channel (PUSCH) , or a sounding reference signal (SRS) or receive on a physical downlink control channel (PDCCH) , a physical downlink shared channel (PDSCH) , a tracking reference signal (TRS) or a channel state information reference signal (CSI-RS) on SSB symbols that are to be measured within an SMTC window duration.

In addition to performing L3 measurements, such as RRM measurements, a UE also needs to perform Layer 1 (L1) measurements, such as radio link monitoring (RLM) , beam failure detection (BFD) , candidate beam detection (CBD) , and L1-RSRP. These examples are not intended to be limiting. Other types of L1 measurements may also be performed by the UE.

FIG. 11B: UE Beamforming using Layer 1

FIG. 11 B illustrates an example of L3 and L1 measurements of cells in accordance with some embodiments. In order to locate neighbor cells and/or additional beams of a target cell, the UE 106 can perform L3 measurements with a rough beam 1102, having a wider beam width. The UE can then perform L1 measurements using a fine beam 1104 having a narrower beam width relative to the rough beam used for L3 measurements. The UE cannot perform L3 and L1 measurements simultaneously on a single receive chain.

FIG. 12: LTM Procedure

Handover mobility is the process of transferring an ongoing communication session of a UE from one cell to another cell in a connected state. The handover process has been designed to enable continuous connectivity of a mobile UE with the core network (e.g. 1020, FIG. 10) as the UE moves between different cells in the network. Mobility can be categorized into two types: beam level mobility and cell level mobility.

Beam level mobility does not require RRC signaling to be triggered. Handover from one beam to another beam can be performed within a cell or between cells. Beam level mobility can be accomplished using L1 and L2 signaling via the physical layer and the medium access control (MAC) layer control signaling. The UE does not need to use RRC signaling to handover to a new beam.

Cell level mobility, in contrast, does use explicit RRC signaling. The signaling procedure can comprise a handover request sent from a source gNB to a target gNB, a handover request acknowledgment sent from the target gNB to the source gNB, an RRC reconfiguration IE sent from the source gNB to the UE, and an RRC Reconfiguration Complete IE sent from the UE to the target gNB via RRC signaling.

The handover process used for NR has been derived from the process used in 3GPP 4G LTE in which the network controls UE mobility based on UE measurement reporting. The UE can perform RRM measurements of neighboring cells and report the results to the gNB. The gNB can then select the target gNB based on the measurements reported by the gNB.

In FR2, beamforming is used to mitigate high frequency signal loss in the atmosphere. When the UE changes direction or moves away from a beam, signal degradation can occur much more quickly than occurs in cell level mobility. Channel conditions can also degrade quickly when a line of sight link with a cell beam changes. The Layer 3 measurements and reporting using RRC signaling may not occur with sufficient frequency to enable handover to a new beam when signal loss occurs with a target beam.

In Release 18 of the 3GPP NR specification, the concept of lower layer (L1/L2) Triggered Mobility (LTM) was disclosed. LTM can enable a serving cell change using L1/L2 signaling, while maintaining the configuration of the upper layers. This can decrease latency, and reduce the amount of overhead and potential downtime during handover.

FIG. 12 provides an example procedure 1200 for LTM. Steps 1 through 3 comprise a preparation for LTM to occur. In the first step, the UE, which is in an RRC connected state with the base station (gNB) , can send a measurement report to the base station. This measurement report is a Layer 3 measurement report. In step 2, the base station can then send an RRC reconfiguration message to the UE with an LTM candidate cell configuration of one or multiple candidate cells, based, at least in part, on the information received in the measurement report sent to the base station in step 1. In step 3, the UE can store the LTM candidate cell configuration (s) and send an RRC reconfiguration complete message to the base station.

Steps 4a and 4b in the example procedure 1200 comprise an early sync process. The UE can then perform DL and UL synchronization with the candidate target cells indicated in the RRC reconfiguration message before receiving a cell switch command. Timing advance acquisition may also be performed by the UE with the candidate target cells.

In steps 5-7 in the example procedure 1200, an LTM cell switch can be executed. In step 5, the UE can perform L1 measurements on the configured candidate cell (s) and transmit L1 measurement reports to the base station. L1 measurement can be performed as long as the RRC reconfiguration (step 2) is applicable. In step 6, the base station can then decide whether to execute an LTM cell switch to one of the candidate target cells. A MAC control element (MAC-CE) can be transmitted from the base station to the UE to trigger an LTM switch. The cell switch can be triggered when the MAC-CE includes the candidate configuration index of the target cell. The UE can detach from the source and switch to the target cell and apply the configuration indicated by the candidate configuration index.

In step 7, the UE can perform a random access channel (RACH) procedure with the target cell if a valid timing advance (TA) for the target cell is not available. The UE can perform a contention free random access (CFRA) procedure with the target cell if the LTM cell switch command MAC CE contains information for CFRA as specified in clause 6.1.3. xy of 3GPP Technical Specification (TS) 38.321 [6] V18.0.0 (January 2024) .

In step 8, the UE can complete the LTM switch procedure by sending an RRC Reconfiguration Complete (RRCReconfigurationComplete) message to the base station indicating that the LTM cell switch by the UE to the target cell was successful. The UE may perform a partial or full MAC reset. The UE can also reestablish radio link control (RLC) messaging and may perform data recovery with the PDCP layer during the cell switch.

The ability to use LTM, with L1 and L2 level signaling to provide cell level mobility can significantly decrease the latency that can occur during a typical handover procedure using L3 level signaling and increase the probability of a successful handover of the UE from one cell to another. However, even a typical LTM process, such as the example procedure 1200 for LTM illustrated in FIG. 12, can still be refined to further decrease latency and increase the probability of a successful handover. The use of Artificial Intelligence (AI) and/or Machine Learning (ML) models in one or more locations within the example procedure 1200 can be used to further enhance the ability of a UE to quickly and efficiently perform handovers using LTM with potentially lower latency and a higher probability of success than using LTM without the AI/ML models.

FIG. 13: AI/ML Model

FIG. 13 provides an example illustration of a generic AI/ML operational workflow for an ML entity. This example workflow was created by the 3GPP work group SA5. The example is not intended to be limiting. Rather, it is used to illustrate an example of a typical workflow for an AI/ML entity. Definitions used to define various aspects of AI/ML are described in 3GGP TS 38.343 V18.0.0 (December 2023) and included herein.

In this example, the workflow comprises four main phases: a training, emulation, deployment, and inference phase. The main task involved in each phase are briefly described in the proceeding paragraphs.

In the training phase, an ML entity is provided with training data. In one embodiment, the ML entity can be a UE-side AI/ML model, also referred to as simply an AI model. The training data can be collected at the UE and sent to the model. The ML training process can also include validation of the trained ML entity to evaluate the performance variance when the ML entity performs on training data and validation data. If the validation result does not meet the expectations, with a level of variance that is not acceptable, the ML entity can be re-trained until the ML entity is validated.

The training phase of the ML entity can also include ML testing of the validated ML entity. Similar to the validation step, testing data can be used to determine how well the ML entity performs. If the testing meets expectations, the ML entity can proceed to the next phase. Otherwise, the ML entity may need to be re-trained and re-validated.

The emulation phase involves running an ML entity or AI/ML inference function for inference in an emulation environment that can be used to evaluate the inference performance of the ML entity or the AI/ML inference function in the emulation environment prior to applying it to a target operational network or system, such as in a UE in a 3GPP network. Data from the emulation phase can be used in both the training phase and the inference phase. In some embodiments, the emulation phase may be considered optional and can be skipped.

The deployment phase involves loading a trained ML entity into the target AI/ML inference function which will be used for inference. If the training function and the inference function are co-located, then the deployment process may not be needed. In one embodiment, the training phase may be performed at a location other than the UE, such as on a server, in the network 1002, or at the base station 102. In this embodiment, the trained ML entity can be transmitted to the UE 106 from the base station 102. Alternatively, if the ML entity is trained at the UE, no deployment may be needed.

In the inference phase, the AI/ML inference function can be used to infer an output for a selected input based on the training data used to train the ML entity.

According to some embodiments, a variety of approaches may be considered for the enhancement of the LTM process. UE-side AI/ML entity can be used to enhance LTM. The UE-side AI/ML entity can be trained using UE mobility history. The training of the AI/ML entity can be UE-based training, network-based training, or joint training that can occur at both the network 1002 and the UE 106. For each different AI/ML entity used in LTM, the UE can be configured with a separate UE capability, thereby enabling the UE 106 to provide information to the base station 102 and network 1002 the ability of the UE to use the AI/ML entity to enhance LTM. As many of the solutions can increase the autonomy of the UE 106 from the network 1002 and base station 102, each AI/ML entity used at the UE 106 for LTM may be enabled by the network 1002. For example, the network can enable the AI/ML entity (s) to operate at the UE using an LTM configuration, such as the RRC configuration in step 2 of FIG. 12.

FIGS. 14-18: UE-based AI/ML enhancements to an LTM procedure

As previously discussed, in step 1 of FIG. 12, the UE 106 can send a measurement report to the base station 102. The measurement report can include measurements made by the UE of various types of reference signals of neighboring cells. The measurements in the measurement report can then be used by the base station to determine whether the LTM process should be performed. Based on this determination, the base station 102 can initiate candidate cell preparation. In step 2 of FIG. 12, the base station encodes and transmits an RRCReconfiguration message to the UE 106 including the LTM candidate cell configurations of one or multiple candidate cells that can be used for LTM. In step 3 of FIG. 12, the UE stores the LTM candidate cell configurations and transmits an RRCReconfigurationComplete message to the base station. Steps 1-3 of FIG. 12 are reproduced in the example illustration of FIG. 14.

As illustrated in FIG. 14, in accordance with some embodiments, an LTM procedure 1400 comprising a UE-based AI/ML model 1404 can be used to enhance an LTM process. In this example, the UE-side AI/ML model 1404 can be configured to determine LTM candidate cells and/or neighboring cells that operate above a selected performance threshold in accordance with some embodiments. In addition, the UE-side AI/ML model 1404 can be used to identify when there are additional, better LTM candidate cells that were not configured by the network. For instance, the UE-side AI/ML model 1404 may output an inference regarding a probability for each LTM candidate cell or neighboring cell not included in the LTM candidate cells, indicating a probability that the LTM candidate cell or neighboring cell is capable of supporting the UE in a handover. A threshold level may be selected by the UE 106 or the threshold can be provided by the network 1002. The LTM candidate cells or neighboring cells having a probability greater than the threshold can be identified as the LTM candidate cells that are available for handover and may be added to the LTM candidate cell configurations received from the base station 102 that can be used for LTM. The LTM candidate cells having a probability less than the threshold value may be identified as sub-optimal and can be removed from the LTM candidate cell configurations, received from the base station 102, that are used for LTM.

In one example, the network 1002 can use the RRCReconfiguration message transmitted from the base station 102 to the UE 106 in step 2 to further include an indication to configure the UE to provide a UE LTM candidate message with a recommendation to the network 1002, if the UE is capable of providing the recommendation. The network 1002 can also use the RRCReconfiguration message to indicate whether the UE LTM candidate message is for training the AI/ML model 1404, used for AI/ML model verification, or used for actual mobility (i.e. handover using LTM) .

In some embodiments, the UE 106 can provide a recommendation to the base station 102 about which LTM candidate cells can be added and which LTM candidate cells can be removed from the list of LTM candidate cell configurations of the one or multiple candidate cells provided by the base station 102 in step 2. In one example, the UE recommendation can be included in the RRCReconfigurationComplete message sent in step 3. The LTM candidate cells to remove can be a list of LTM candidate identifications (IDs) , in a message that can be called an LTM-CandidateId message. The LTM candidate cells to add can be a list of physical cell IDs, in a message that may be called PhysCellId. The network 1002 may then provide a new LTM configuration in Step 2, and repeat Step 3.

Alternatively, the UE 106 may provide the recommendation to the base station about which LTM candidate cells can be added prior to Step 2. In this example, UE Assistance Information (UAI) signaling 1406 can be used by the UE 106 to send the recommendation to the base station 102 such as, for example, by sending the PhysCellId message 1402, containing a list of cell IDs of the LTM candidate cells to be added and/or the LTM candidate identifications (IDs) in the LTM-CandidateId message for the candidate cells to be removed. The UAI can be sent from the UE 106 to the network 1002 via the base station 102 using UAI signaling.

In another alternative example, the UE-based AI/ML model inference results may not be ready at the point of Step 3. In this example, the UE 106 can send the suggested candidate list about which LTM candidate cells can be added between steps 3 and 5 (See also, FIG. 12) . In this example, UAI signaling can be used by the UE 106 to send the recommendation regarding which LTM candidate cells can be added to the base station 102 such as, for example, by sending the UAI PhysCellId message 1406, containing a list of cell IDs of the LTM candidate cells to be added, from the UE 106 to the network 1002 via the base station 102 using UAI signaling.

The ability to use a UE-side AI/ML model 1404 to update the LTM candidate cells can enhance the LTM procedure 1400 and result in fewer radio link failures. In addition, with the UE assisting in selecting the LTM candidate cell that may be used for LTM, fewer measurements may be made at the UE and result in a power savings at the UE, fewer measurements to perform, and fewer candidate cells for the network to prepare, thereby decreasing the use of network resources.

In another embodiment, a UE-based AI/ML model 1604 can be used to infer when an LTM cell switch will be executed at the UE, as illustrated in FIG. 16. A legacy LTM cell switch is illustrated in steps 5 and 6 of FIG. 12. In step 5 of FIG. 12, an L1 measurement report is sent from the UE 106 to the base station 102. In step 6 of FIG. 12, based, at least in part, on the data in the L1 measurement report, the base station 102 can send a cell switch command to the UE 106, using a medium access control (MAC) control element (MAC_CE) .

In some embodiments, the Step 2 legacy RRC reconfiguration message received from the base station 102 at the UE 106 can further comprise an indication from the network 1002 that the UE 106 is configured for an autonomous cell switch decision.

In some embodiments, as illustrated in FIG. 15, an LTM procedure 1500 comprising a UE-based AI/ML model 1504 can be trained with data that is used to infer when the UE will receive a cell switch command based, at least in part, on the data contained in the L1 measurement report 1502. A successfully trained AI/ML model 1504 can have at least a portion of the L1 measurement report input to the AI/ML model 1504, and use the information, at least in part, to output an inference that the UE will perform a cell switch. In one example, the output can be a probability that an LTM cell switch will occur. Based on the output of the AI/ML model, the UE can make an LTM decision 1506 on whether to perform a cell switch. When the probability output by the AI/ML model is greater than a threshold level, the UE can be configured to autonomously perform the cell switch. The threshold level may be determined at the UE 106. Alternatively, the threshold level may be sent from the network 1002 or determined by the base station 102 and communicated to the UE. The threshold level may be included in the RRC reconfiguration message in step 2. When the network 1002 is satisfied with the accuracy of the AI/ML model, the network can enable the UE to make autonomous LTM cell switching decisions based on the output of the AI/ML model. The autonomous LTM cell switching may be configured per LTM candidate configuration of for all LTM configurations.

The use of the AI/ML model 1504 to infer when LTM cell switching will occur can reduce latency in the LTM procedure 1500 and also reduce signaling over the air interface. For example, with respect to the legacy LTM procedure 1200, steps 5 and 6 of FIG. 12 may not be used in the LTM procedure 1500 illustrated in the example of FIG. 15. The time used to send the L1 measurement report in step 5 and receive the cell switch command in step 6 is not needed in the LTM procedure 1500.

In the legacy LTM procedure 1200 of FIG. 12, a list of transmission configuration indicator (TCI) states can be provided in the RRC reconfiguration message in step 2 for each candidate LTM configuration. In step 6, the network 1002 indicates which TCI state the UE 106 shall activate in the cell switch command sent via MAC CE from the base station 102 to the UE 106.

In some embodiments, a UE-side AI/ML model 1604 can be trained to infer a best TCI state for the UE to activate in the cell switch command in step 6, as illustrated in the example LTM procedure 1600 illustrated in FIG. 16. In one embodiment, the AI/ML model 1604 can be trained at the network 1002 or using data from the UE and the network. For example, the AI/ML model 1604 can be trained using the list of TCI states provided in the RRC reconfiguration message in step 2 for each candidate LTM configuration, and the eventual indicated TCI state sent from the network (in step 6 of the legacy LTM procedure in FIG. 12) that the UE is to activate.

In one example, the network 1002 can send, via the base station 102, an indication in the RRC reconfiguration message of step 2 indicating that the UE can autonomously select a TCI state, or an indication that the UE can provide a recommendation to the network as a suggested TCI state to activate. The recommended TCI state output from the AI/ML model 1604 can be communicated from the UE 106 to the network 1002, via the base station 102, in Step 5 of the LTM procedure 1600 as part of the L1 measurement report. Alternatively (or additionally) , the TCI state suggestion output from the AI/ML model can be communicated from the UE 102 to the network 1002, via the base station 102, in step 3 in the RRC reconfiguration complete message in the LTM procedure 1600. In another alternative, the suggested TCI state to activate that is output from the AI/ML model 1604 can be communicated from the UE 106 to the network 1002, via the base station 1002, using UAI signaling 1606. While the UAI signaling 1606 is illustrated as occurring after the L1 Measurement report sent in Step 5, this is not intended to be limiting. The UAI signaling 1606 used to send the suggested TCI state to activate to the network can be sent at a selected time after receiving the RRC reconfiguration message in step 2 for each candidate LTM configuration

In some embodiments, the LTM procedure 1200 does not configure the UE 106 for early timing advance (TA) acquisition. When this occurs, the UE can obtain the TA of the target cell when performing the RACH procedure in step 7. However, obtaining the TA of the target cell through the RACH procedure can increase latency. When the UE is configured for UE-based TA measurement, the UE can acquire the TA value (s) of the candidate cell (s) by measuring them. Otherwise, the UE can perform early TA acquisition with the candidate cell (s) as requested by the network before receiving the cell switch command, such as in step 4b of FIG. 12.

A UE-side AI/ML model 1704, as illustrated in the example LTM procedure 1700 illustrated in FIG. 17, can be trained to infer for which cells early TA acquisition will be performed, and what method the TA acquisition will be performed (PDCCH or UE-based TA measurement. The AI/ML model may be configured by the network 1002. The inference output by the trained UE-side AI/ML model 1704 can be communicated from the UE 106 to the network 1002, via the base station 102, to the network 1002 in step 3 as a suggestion to the network. In one example, the inference output from the AI/ML model 1704 and communicated to the network 1002 can be per configured LTM cell candidate. The network may perform steps 2 and 3 again after receiving the inference suggested to the network 1002. Alternatively, the inference output from the AI/ML model 1704 can be communicated to the network 1002 via dedicated RRC signaling using UAI signaling 1706. The use of the AI/ML model 1704 to infer for which cells early TA acquisition will be performed can provide a reduction in latency and more robustness in the LTM procedure with fewer failures.

In some embodiments, while the UE has stored candidate cell configurations, the UE can also execute any L3 handover command sent by the network 1002 via the base station 102 to the UE 106. In other words, both LTM and L3 mobility can be configured simultaneously. Accordingly, a UE, which has been configured with both measurements for L3 handover, and LTM candidates, can send an indication to the network 1002 via the base station 102 whether the UE 106 prefers an L3 handover or LTM. As illustrated in the example of FIG. 18, a UE-side AI/ML model 1804 can be trained to identify, when the UE has received information for both an LTM process 1800 and performed L3 measurements of neighboring cells, when an L3 handover or an LTM would be more beneficial to the UE. For example, the AL/ML model may be trained to identify when an L3 handover or LTM would be more beneficial to the UE 106 based on the latency caused by the L3 handover relative to the LTM process, the probability of radio link failure (RLF) , the probability of beam failure (BF) , and determine which type of handover may be performed. The UE 106 can then send a handover type indication to the network 1002 via the base station 102 using the RRC reconfiguration complete message or a UAI message 1806 that can be sent at some point in the LTM process 1800 or the LTM process 1200 illustrated in FIG. 12. The handover type can be provided per cell. The indication may be a general preference of the AI/ML model for LTM or L3 handover per cell.

FIG. 19: Flow Chart for AI/ML enhancements for LTM

FIG. 19 illustrates an example flow chart of a method of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a user equipment (UE) using artificial intelligence (AI) or machine learning (ML) , according to some embodiments. The method shown in FIG. 19 may be used in conjunction with any of the systems, methods, or devices illustrated in the Figures, among other devices. In various embodiments, some of the method elements shown may be performed concurrently, in a different order than shown, or may be omitted. Additional method elements may also be performed as desired.

In accordance with an embodiment, a method 1900 may encode, at the UE, a measurement report for transmission from the UE to a base station using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report, as shown in block 1910. A radio resource control (RRC) reconfiguration message received from the base station can be decoded at the UE, as shown in block 1920. The RRC reconfiguration message can include an LTM candidate cell configuration list. An RRC reconfiguration complete message can be encoded at the UE for transmission from the UE to the base station, as shown in block 1930. The method 1900 can further comprise determining, at the UE, an enhancement to the LTM based on an inference output from the AI model at the UE, as shown in block 1940. A cell switch can be executed at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE, as shown in block 1950.

Examples of Systems, Apparatuses, and Methods

The following examples pertain to specific technology embodiments and point out specific features, elements, or actions that can be used or otherwise combined in achieving such embodiments.

Example 1 is directed to a method of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a user equipment (UE) using an artificial intelligence (AI) model, the method comprising: encoding, at the UE, a measurement report for transmission from the UE to a base station using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report; decoding, at the UE, a radio resource control (RRC) reconfiguration message received from the base station, wherein the RRC reconfiguration message includes an LTM candidate cell configuration list; encoding, at the UE, an RRC reconfiguration complete message for transmission from the UE to the base station; determining, at the UE, an enhancement to the LTM based on an inference output from the AI model at the UE; and executing a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.

Example 2 includes the method of Example 1, wherein the enhancement comprises configuring the AI model with the LTM candidate cell configurations to enable the AI model to output a probability of one or more LTM candidate cells, in the LTM candidate cell configuration list, being capable of supporting the UE in a handover.

Example 3 includes the method of Example 2, further comprising configuring the AI model with one or more neighboring cells of the UE, wherein the neighboring cells are not included in the LTM candidate cell configuration list, and the AI model is configured to output a probability that the one or more neighboring cell is capable of supporting the UE in a handover.

Example 4 includes the method of Examples 2 or 3, further comprising determining a threshold level for the probability at the UE or receiving the threshold level at the UE from the base station, wherein: the one or more LTM candidate cells in the LTM candidate cell configuration list having a probability less than the threshold are removed from the LTM candidate cell configuration list; or the one or more neighboring cells having a probability greater than the threshold are added to the LTM candidate cell configuration list as an LTM candidate cell.

Example 5 includes the method of Example 4, further comprising generating, at the UE, an LTM candidate cell list comprising adding one or more of the LTM candidate cells having a probability greater than the threshold or one or more of the neighboring cells having a probability greater than the threshold to an LTM candidate identification (LTMCandidateId) list that includes a physical cell ID (PhysCellId) of the LTM candidate cells or the neighboring cells in the LTM Candidate ID list, wherein the LTM Candidate ID list is sent as an LTMCandidateID message.

Example 6 includes the method of claim 5, wherein the LTMCandidateId message is encoded for transmission from the UE to the base station in: the RRC reconfiguration complete message; or a UE assistance information (UAI) message, wherein the UAI message is sent from the UE prior to decoding the RRC reconfiguration message or after encoding the RRC reconfiguration complete message.

Example 7 includes the method of Example 6, further comprising, after transmitting the LTMCandidateId message: decoding, at the UE, an updated RRC reconfiguration message received from the base station; and encoding, at the UE, an updated RRC reconfiguration complete message for transmission from the UE to the base station.

Example 8 includes the method of Example 1, further comprising: decoding, at the UE, the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to provide a UE LTM candidate message with a recommendation of one or more LTM candidate cells to a network via the base station; decoding, at the UE, the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication that the UE LTM candidate message is for one or more of: training the AI model; or verification of the AI model; or executing LTM at the UE; or encoding, at the UE, a capability message indicating to the network that the UE is capable of providing the UE LTM candidate message with the recommendation of the one or more LTM candidate cells to the network.

Example 9 includes the method of Example 1, further comprising decoding, at the UE the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to perform an autonomous LTM cell switch decision.

Example 10 includes the method of Example 1, further comprising configuring the AI model with an L1 measurement report input to the AI model at the UE to enable the AI model to output a decision that the UE will perform an autonomous LTM cell switch without receiving a cell switch command from the base station for an LTM cell switch.

Example 11 includes the method of Example 10, further comprising configuring the AI model with the L1 measurement report to enable the AI model to output a probability of the autonomous LTM cell switch to be executed at the UE.

Example 12 includes the method of Examples 10 or 11, further comprising determining a threshold level for the probability at the UE or receiving the threshold level at the UE from the base station.

Example 13 includes the method of any of Examples 10 to 12, further comprising receiving the threshold level at the UE from the base station via the RRC reconfiguration message.

Example 14 includes the method of any of Examples 10 to 13, wherein the autonomous LTM cell switch to be executed at the UE is configured by the AI model per LTM candidate cell in the LTM candidate cell configuration list.

Example 15 includes the method of Example 1, further comprising configuring the AI model to infer a transmission configuration indicator (TCI) state for the UE to activate at the cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list.

Example 16 includes the method of Example 15, further comprising training the AI model using a list of TCI states provided in the RRC reconfiguration message for each LTM candidate cell in the LTM candidate cell configuration list.

Example 17 includes the method of Examples 1 or 15 or 16, further comprising decoding, at the UE the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to autonomously select the TCI state to activate or to configure the UE to provide a recommendation to the network as a suggested TCI state to activate.

Example 18 includes the method of any of Examples 15 to 17, further comprising sending the TCI state from the AI model to a network via the base station in: a Layer 1 (L1) measurement report; or the RRC reconfiguration complete message; or in a UE assistance information (UAI) RRC message.

Example 19 includes the method of Example 1, further comprising configuring the AI model to infer for which one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early timing advance (TA) acquisition on.

Example 20 includes the method of Example 19, further comprising encoding, for transmission from the UE to the base station, the RRC reconfiguration complete message, wherein the RRC reconfiguration complete message includes the output of the AI model to infer for which of the one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early TA acquisition on.

Example 21 includes the method of Examples 19 to 20, wherein the inference for which of the one or more LTM candidate cells in the LTM candidate cell configuration list that the UE will perform an early timing advance (TA) acquisition on is configured by the AI model per LTM candidate cell in the LTM candidate cell configuration list.

Example 22 includes the method of Example 20, further comprising, after transmitting the LTM candidate cells in the LTM candidate cell configuration list that the UE will perform the early TA acquisition on: decoding an updated RRC reconfiguration message received from the base station; and encoding an updated RRC reconfiguration complete message for transmission from the UE to the base station.

Example 23 includes the method of Example 19, further comprising encoding, for transmission from the UE to the base station, a UE assistance information (UAI) message comprising the inference for which of the one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early TA acquisition on.

Example 24 includes the method of Example 1, further comprising configuring the AI model to infer a handover type comprising when a Layer 3 (L3) handover or an LTM will be used by the UE .

Example 25 includes the method of Example 24, further comprising encoding, for transmission from the UE to the base station a handover type indication based on the inference of the handover type from the AI model, wherein the indication is sent using the RRC reconfiguration complete message or a UE assistance information (UAI) message.

Example 26 includes the method of Examples 24 or 25, wherein the handover type is inferred by the AI model per LTM candidate cell in the LTM candidate cell configuration list.

A computer program product is disclosed herein, comprising computer instructions which, when executed by one or more processors, perform any of the operations described in the examples above.

Embodiments of the present disclosure may be realized in any of various forms. For example, some embodiments may be realized as a computer-implemented method, a computer readable memory medium, or a computer system. Other embodiments may be realized using one or more custom-designed hardware devices such as ASICs. Still other embodiments may be realized using one or more programmable hardware elements such as FPGAs.

In some embodiments, a non-transitory computer-readable memory medium may be configured so that it stores program instructions and/or data, where the program instructions, if executed by a computer system, cause the computer system to perform a method, e.g., any of the method embodiments described herein, or, any combination of the method embodiments described herein, or, any subset of any of the method embodiments described herein, or, any combination of such subsets.

In some embodiments, a device (e.g., a UE 106) may be configured to include a processor (or a set of processors) and a memory medium, where the memory medium stores program instructions, where the processor is configured to read and execute the program instructions from the memory medium, where the program instructions are executable to implement any of the various method embodiments described herein (or, any combination of the method embodiments described herein, or, any subset of any of the method embodiments described herein, or, any combination of such subsets) . The device may be realized in any of various forms.

Any of the methods described herein for operating a user equipment (UE) may be the basis of a corresponding method for operating a base station, by interpreting each message/signal X received by the UE in the downlink as message/signal X transmitted by the base station, and each message/signal Y transmitted in the uplink by the UE as a message/signal Y received by the base station.

Although the embodiments above have been described in considerable detail, numerous variations and modifications will become apparent to those skilled in the art once the above disclosure is fully appreciated. It is intended that the following claims be interpreted to embrace all such variations and modifications.

Claims

A method of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a user equipment (UE) using an artificial intelligence (AI) model, the method comprising:

encoding, at the UE, a measurement report for transmission from the UE to a base station using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report;

decoding, at the UE, a radio resource control (RRC) reconfiguration message received from the base station, wherein the RRC reconfiguration message includes an LTM candidate cell configuration list;

encoding, at the UE, an RRC reconfiguration complete message for transmission from the UE to the base station;

determining, at the UE, an enhancement to the LTM based on an inference output from the AI model at the UE; and

executing a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on the inference output from the AI model at the UE.
The method of claim 1, wherein the enhancement comprises configuring the AI model with the LTM candidate cell configurations to enable the AI model to output a probability of one or more LTM candidate cells, in the LTM candidate cell configuration list, being capable of supporting the UE in a handover.
The method of claim 2, further comprising configuring the AI model with one or more neighboring cells of the UE, wherein the neighboring cells are not included in the LTM candidate cell configuration list, and the AI model is configured to output a probability that the one or more neighboring cells is capable of supporting the UE in a handover.
The method of claims 2 or 3, further comprising determining a threshold level for the probability at the UE or receiving the threshold level at the UE from the base station, wherein:

the one or more LTM candidate cells in the LTM candidate cell configuration list having a probability less than the threshold are removed from the LTM candidate cell configuration list; or

the one or more neighboring cells having a probability greater than the threshold are added to the LTM candidate cell configuration list as an LTM candidate cell.
The method of claim 4, further comprising generating, at the UE, an LTM candidate cell list comprising adding one or more of the LTM candidate cells having a probability greater than the threshold or one or more of the neighboring cells having a probability greater than the threshold to an LTM candidate identification (LTMCandidateId) list that includes a physical cell ID (PhysCellId) of the LTM candidate cells or the neighboring cells in the LTM Candidate ID list, wherein the LTM Candidate ID list is sent as an LTMCandidateID message.
The method of claim 5, wherein the LTMCandidateId message is encoded for transmission from the UE to the base station in:

the RRC reconfiguration complete message; or

a UE assistance information (UAI) message, wherein the UAI message is sent from the UE prior to decoding the RRC reconfiguration message or after encoding the RRC reconfiguration complete message.
The method of claim 6, further comprising, after transmitting the LTMCandidateId message:

decoding, at the UE, an updated RRC reconfiguration message received from the base station;

encoding, at the UE, an updated RRC reconfiguration complete message for transmission from the UE to the base station.
The method of claim 1, further comprising:

decoding, at the UE, the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to provide a UE LTM candidate message with a recommendation of one or more LTM candidate cells to a network via the base station;

decoding, at the UE, the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication that the UE LTM candidate message is for one or more of:

training the AI model; or

verification of the AI model; or

executing LTM at the UE; or

encoding, at the UE, a capability message indicating to the network that the UE is capable of providing the UE LTM candidate message with the recommendation of the one or more LTM candidate cells to the network.
The method of claim 1, further comprising decoding, at the UE the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to perform an autonomous LTM cell switch decision.
The method of claim 1, further comprising configuring the AI model with an L1 measurement report input to the AI model at the UE to enable the AI model to output a decision that the UE will perform an autonomous LTM cell switch without receiving a cell switch command from the base station for an LTM cell switch.
The method of claim 10, further comprising configuring the AI model with the L1 measurement report to enable the AI model to output a probability of the autonomous LTM cell switch to be executed at the UE.
The method of claims 10 or 11, further comprising determining a threshold level for the probability at the UE or receiving the threshold level at the UE from the base station.
The method of any of claims 10 to 12, further comprising receiving the threshold level at the UE from the base station via the RRC reconfiguration message.
The method of any of claims 10 to 13, wherein the autonomous LTM cell switch to be executed at the UE is configured by the AI model per LTM candidate cell in the LTM candidate cell configuration list.
The method of claim 1, further comprising configuring the AI model to infer a transmission configuration indicator (TCI) state for the UE to activate at the cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list.
The method of claim 15, further comprising training the AI model using a list of TCI states provided in the RRC reconfiguration message for each LTM candidate cell in the LTM candidate cell configuration list.
The method of claims 1 or 15 or 16, further comprising decoding, at the UE the RRC reconfiguration message received from the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to autonomously select the TCI state to activate or to configure the UE to provide a recommendation to a network as a suggested TCI state to activate.
The method of any of claims 15 to 17, further comprising sending the TCI state from the AI model to a network via the base station in:

a Layer 1 (L1) measurement report; or

the RRC reconfiguration complete message; or

in a UE assistance information (UAI) RRC message.
The method of claim 1, further comprising configuring the AI model to infer for which one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early timing advance (TA) acquisition on.
The method of claim 19, further comprising encoding, for transmission from the UE to the base station, the RRC reconfiguration complete message, wherein the RRC reconfiguration complete message includes the output of the AI model to infer for which of the one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early TA acquisition on.
The method of any of claims 19 to 20, wherein the inference for which of the one or more LTM candidate cells in the LTM candidate cell configuration list that the UE will perform an early timing advance (TA) acquisition on is configured by the AI model per LTM candidate cell in the LTM candidate cell configuration list.
The method of claims 20, further comprising, after transmitting the LTM candidate cells in the LTM candidate cell configuration list that the UE will perform the early TA acquisition on:

decoding an updated RRC reconfiguration message received from the base station; and

encoding an updated RRC reconfiguration complete message for transmission from the UE to the base station.
The method of claim 19, further comprising encoding, for transmission from the UE to the base station, a UE assistance information (UAI) message comprising the inference for which of the one or more LTM candidate cells in the LTM candidate cell configuration list the UE will perform an early TA acquisition on.
The method of claim 1, further comprising configuring the AI model to infer a handover type comprising when a Layer 3 (L3) handover or an LTM will be used by the UE .
The method of claim 24, further comprising encoding, for transmission from the UE to the base station a handover type indication based on the inference of the handover type from the AI model, wherein the indication is sent using the RRC reconfiguration complete message or a UE assistance information (UAI) message.
The method of claims 24 or 25, wherein the handover type is inferred by the AI model per LTM candidate cell in the LTM candidate cell configuration list.
An apparatus configured to cause a user equipment (UE) to perform any of the methods of claims 1 to 26.
A baseband processor configured to perform one or more of the method claims 1 to 26.
A base station configured to perform any of the operations described herein.
A computer program product, comprising computer instructions which, when executed by one or more processors, perform any of the operations described herein.
A method of enhancing Layer 1 or Layer 2 Triggered Mobility (LTM) at a network for a user equipment (UE) using an artificial intelligence (AI) model, the method comprising:

receiving, at the network from the UE, a measurement report for transmission using radio resource control (RRC) messaging to enable the base station to initiate candidate cell preparation based on the measurement report;

sending, from the network to the UE, a radio resource control (RRC) reconfiguration message, wherein the RRC reconfiguration message includes an LTM candidate cell configuration list;

receiving, at the network, an RRC reconfiguration complete message from the UE;

sending, to the UE, an enhancement to the LTM based on an inference output from an AI model to enable the UE to execute a cell switch at the UE to an LTM candidate cell in the LTM candidate cell configuration list based, at least in part, on an inference output from the AI model.
The method of claim 31, wherein the enhancement comprises configuring the AI model with the LTM candidate cell configurations to enable the AI model to output a probability of one or more LTM candidate cells, in the LTM candidate cell configuration list, being capable of supporting the UE in a handover.
The method of claim 32, further comprising configuring the AI model with one or more neighboring cells of the UE, wherein the neighboring cells are not included in the LTM candidate cell configuration list, and the AI model is configured to output a probability that the one or more neighboring cells is capable of supporting the UE in a handover.
The method of claims 32 or 33, further comprising determining a threshold level for the probability at the UE or sending the threshold level to the UE from the network via a base station, wherein:

the one or more LTM candidate cells in the LTM candidate cell configuration list having a probability less than the threshold are removed from the LTM candidate cell configuration list; or

the one or more neighboring cells having a probability greater than the threshold are added to the LTM candidate cell configuration list as an LTM candidate cell.
The method of claim 34, further comprising generating, at the UE, an LTM candidate cell list comprising adding one or more of the LTM candidate cells having a probability greater than the threshold or one or more of the neighboring cells having a probability greater than the threshold to an LTM candidate identification (LTMCandidateId) list that includes a physical cell ID (PhysCellId) of the LTM candidate cells or the neighboring cells in the LTM Candidate ID list, wherein the LTM Candidate ID list is received at the network from the UE as an LTMCandidateID message.
The method of claim 35, wherein the LTMCandidateId message is received at the network in:

the RRC reconfiguration complete message; or

a UE assistance information (UAI) message, wherein the UAI message is sent from the UE prior to decoding the RRC reconfiguration message or after encoding the RRC reconfiguration complete message.
The method of claim 36, further comprising, after receivng the LTMCandidateId message:

transmitting, to the UE, an updated RRC reconfiguration message received via the base station;

receiving, at the network, an updated RRC reconfiguration complete message from the UE.
The method of claim 31, further comprising:

transmitting, to the UE, the RRC reconfiguration message received via a base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to provide a UE LTM candidate message with a recommendation of one or more LTM candidate cells to a network via the base station;

transmitting, to the UE, the RRC reconfiguration message via the base station, wherein the RRC reconfiguration message further comprises an indication that the UE LTM candidate message is for one or more of:

training the AI model; or

verification of the AI model; or

executing LTM at the UE; or

receiving, from the UE, a capability message indicating to the network that the UE is capable of providing the UE LTM candidate message with the recommendation of the one or more LTM candidate cells to the network.
The method of claim 31, further comprising transmitting, to the UE the RRC reconfiguration message via the base station, wherein the RRC reconfiguration message further comprises an indication to configure the UE to perform an autonomous LTM cell switch decision.