WO2025239914A1 - Uplink data based channel estimation in nb-iot physical layer - Google Patents

Abstract

Embodiments disclosed herein provide a method and system for receiving, at a BS and from a UE, first and second control messages associated with first and second communication blocks, respectively. Further, at least one first control element and at least one second control element is extracted from the first and the second communication blocks, respectively. Thereafter, one or more carrier frequency offset (CFO) estimates are obtained based on the first and second control elements. Further, a weighted moving average of the one or more CFO estimates is performed to generate a decision value. The BS also determine that the decision value is above a frequency offset (FO) predetermined threshold. Thereafter, characteristics of the communication channel are estimated based on the determining that the decision value is above the FO predetermined threshold and based on the output value.

Description

UPLINK DATA BASED CHANNEL ESTIMATION IN NB-IOT PHYSICAL LAYER

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to Indian Application No. 202441037729 filed on May 14, 2024 the disclosure of which is incorporated by reference herein in its entirety⁷.

TECHNICAL FIELD

[0002] The present disclosure generally relates to the field of wireless communication, and more particularly relates to performing uplink data based channel estimation in a Narrow Band (NB) Internet of Things (loT) physical layer.

BACKGROUND

[0003] The information disclosed in this background section is only for enhancement of understanding of the general background of the disclosure and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

[0004] NB-IoT is a wireless communication technology based on lower power wireless defining a physical layer and a protocol stack supporting various loT devices and applications. NB-IoT operates on multiple frequency bands, suitable for extended coverage, power device complexity and higher data rates. It incorporates technologies such as transmission repetitions, various bandwidth allocation strategies and configurations for uplink transmissions, beamforming, massive Multiple-Input Multiple-Output (M1M0), and dynamic spectrum sharing to enhance performance and efficiency of the communication network. In addition to the above, NB-IoT supports reduced power consumption of the connected loT devices while leveraging the above-stated techniques to enhance overall system capacity with wider coverage. [0005] NB-IoT includes a Narrowband Physical Uplink Shared Channel (NPUSCH) for transmitting uplink user data and control information from a User Equipment (UE) to a Base Station (BS). In NB loT communication network, examples of the UE may include, but are not limited to, parking sensors, smart power meters, pet tracking sensors, motion sensors, etc. Precisely, in the NB-IOT applications, NPUSCH supports two transmission formats NPUSCH Format-1 and NPUSCH Format-2. NPUSCH Format-1 is used for carrying uplink data and NPUSCH Format-2 is intended to transmit UE's Uplink Control data to the base station. For example, NPUSCH Format-2 may be used for signaling acknowledgement information, such as HARQ Ack, for Narrowband Physical Downlink Shared Channel (NPDSCH). NPUSCH Format-2 may use repetition code for error correction and may include a plurality of symbols per slot including a subset of symbols used as DeModulation Reference Signal (DMRS) and another subset of data symbols.

[0006] However, in the NB-IOT applications, there may be scenarios in which the UE from which signals are to be obtained are placed at such location from where it is difficult for the base station to detect the signals with low signal-to-noise ratio (SNR). For example, equipment/sensors, such as parking sensors which are placed in basements, etc. from which uplink signals are to be obtained by the base station. In such scenarios, existing methods of channel estimation to separate the noise/interference from Uplink signal are not sufficient. In addition, they cater additional problems including failure to consider carrier frequency offset (CFO) estimates obtained of previous NPUSCH blocks, associated with previous resource units (RUs), causing accuracy issues in the channel estimation. Further, existing techniques also required large memory requirement for storing Log Likelihood Ratios (LLR) values obtained from each RU. Therefore, when the CFO and TO estimates of the previous NPUSCH block are not considered for the channel estimation, overall channel estimate accuracy is low at lower SNRs. In other words, mean squared error (MSE) for channel estimates are high at the lower SNRs. Moreover, Signal to Interference plus Noise Ratio (SINR) threshold for Discontinuous Transmission (DTX) detection and the CFO/TO estimation are not based on interference level which can dynamically change across cells. In this case as well, the MSE for the channel estimates are high at the lower SNRs. Thus, the channel estimation accuracy is reduced. SUMMARY

[0007] The present disclosure relates to a method comprising the steps of receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block. Further, the first network entity is in communication with the second network entity via a communication channel. At least one first control element and at least one second control element are extracted from the first communication block and the second communication block, respectively. Furthermore, one or more carrier frequency offset (CFO) estimates are obtained based on the at least one first control element and the at least one second control element. Moreover, a weighted moving average of the one or more CFO estimates is performed to generate a decision value. The method also involves detenmning that the decision value is above a frequency offset (FO) predetermined threshold. Based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel are estimated based on the decision value.

[0008] The present disclosure also relates to an apparatus configured to receive, at a first network entity and from a second network entity a first control message associated with a first communication block and a second control message associated with a second communication block. The first network entity is in communication with the second network entity via a communication channel. Further, at least one first control element and at least one second control element are extracted from the first communication block and the second communication block, respectively. Furthemiore. one or more carrier frequency offset (CFO) estimates are obtained based on the at least one first control element and the at least one second control element. Furthermore, a weighted moving average of the one or more CFO estimates is performed to generate a decision value. The apparatus is also configured to determine that the decision value is above a frequency offset (FO) predetermined threshold. Based on the detemiining that the decision value is above the FO predetermined threshold, characteristics of the communication channel are estimated based on the output value.

[0009] In an embodiment, there is a non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor, cause the at least one processor to perform operations of receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block. Further, the first network entity is in communication with the second network entity via a communication channel. At least one first control element and at least one second control element are extracted from the first communication block and the second communication block, respectively. Furthermore, one or more carrier frequency offset (CFO) estimates are obtained based on the at least one first control element and the at least one second control element. Moreover, a weighted moving average of the one or more CFO estimates is performed to generate a decision value. The at least one processor also perform operations of determining that the decision value is above a frequency offset (FO) predetermined threshold. Based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel are estimated based on the decision value.

[0010] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Features, aspects, and advantages of embodiments of the disclosure will be described below with reference to the accompanying drawings, in which like reference numerals denote like elements, and wherein:

[0012] Figs. 1 illustrate an exemplary environment for performing channel estimation in NB- loT physical layer, in accordance with some embodiments of the present disclosure.

[0013] Fig. 2 illustrates a block diagram of the base station for performing channel estimation, in accordance with an embodiment of the present disclosure.

[0014] Fig. 3 shows an exemplary flow chart illustrating method steps for performing channel estimation in the NB-IoT physical layer, in accordance with some embodiments of the present disclosure. [0015] FIG. 4 illustrates an embodiment of a device wherein the method for performing channel estimation in the NB-IoT physical layer may be implemented, according to the embodiments as disclosed herein.

[0016] It should be appreciated by those skilled in the art that any block diagram herein represents conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION OF THE DISCLOSURE

[0017] The following detailed description of example embodiments refers to the accompanying drawings. The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. Further, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). Additionally, the flowchart and description of operations provided below relate to one of the various embodiments. It should be noted that it is possible to make other embodiments that do not exactly match the flowchart and its description. It is understood that in other embodiments one or more operations may be omitted, one or more operations may be added, one or more operations may be performed simultaneously (at least in part).

[0018] It will be apparent that systems and/or methods, described herein, may be implemented in different forms of hardware, software, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and/or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and/or methods are described herein without reference to specific software code. It is understood that software and hardware may be designed to implement the systems and/or methods based on the description herein. [0019] Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of implementations includes each dependent claim in combination with every other claim in the claim set.

[0020] No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items, and may be used interchangeably with “one or more.” Also, as used herein, the terms “has,” “have,” “having,” “include,” “including,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Furthermore, expressions such as “at least one of [A] and [B] ,” “[A] and/or [B] ,” or “at least one of [A] or [B]” are to be understood as including only A. only B, or both A and B.

[0021] The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations.

[0022] In general, channel estimation plays a critical role in achieving reliable communication with high data rates for NB-IoT applications. The base station, associated with the NB-IoT applications, may process uplink control data received from one or more of UEs viaNPUSCH Format-2 carrying essential control information for estimating a channel. However, as stated earlier, in certain scenarios in NB-IOT applications, one or more UEs are placed at such a location from where it is difficult to detect the signals. In such scenarios, the quality of received uplink control signals is drastically reduced, causing degradation of accuracy with which channel estimation for the received uplink control signals is performed.

[0023] The methods and systems of the present disclosure solve a technical problem for estimating channel based on uplink data received from NB loT UEs with sufficient accuracy. Herein, techniques or mechanism may be required such that channel estimation may be performed with sufficient accuracy and reliability. The present disclosure solves this technical problem as described in below embodiments.

[0024] Embodiments disclosed herein provide a method and system for performing accurate channel estimation by performing weighted moving average of CFO estimates across blocks for the same UE using both DMRS and data symbols. Further, various embodiments disclosed herein, allow combining LLR values pertaining to different RUs by averaging across each RU’s. Therefore, the present disclosure suggests techniques for performing channel estimation based on the uplink data at the base station.

[0025] Thus, the present disclosure enables the base station to perform accurate channel estimation.

[0026] FIG. 1 illustrates an exemplar}⁷ environment for performing channel estimation in NB- loT physical layer, in accordance with some embodiments of the present disclosure.

[0027] As shown in FIG. 1, the exemplary' environment 100 includes a Base Station (BS) 101 and a plurality' of User Equipment (UEs) 102a, 102b,..,102n (also referred hereinafter collectively referred to as plurality of UEs 102). The plurality of UEs 102 may refer to the UEs attempting to send a plurality of uplink signals to the BS 101 via a communication network (not shown). In one non-limiting example, each UE 102 of the plurality of UEs 102 is involved in one or more narrow band Internet of things (NB-IoT) applications. As a non-limiting example, the NB-IOT applications may include parking sensor systems, smart buildings with motion sensing system and fire alarms for residential and commercial properties, etc. Each of the plurality of UEs 102 may be, but not limited to a a cellular phone or smart phone, a pager, a laptop computer, a desktop computer, a wireless handset, a portable communication device, a portable computing device (e.g., a personal data assistant), parking sensors which are placed in basements, or any other suitable computing device or other equipment/sensors including a wired or wireless communications interface. According to an embodiment of the present disclosure, the BS 101 is implemented as NB-IoT gNB. Herein, the BS 101 may be partitioned into one or more Central Unit (CU) entities, one or more Distributed Unit (DU) entities, and one or more Radio Units (RUs). In an example, the CU and the DU may be designed to run on or in a ‘‘cloud” environment based on traffic demand. [0028] In an embodiment the BS 101 includes a signal processing system (not shown). The plurality of UEs 102 may send the plurality of uplink signals utilizing a narrowband Physical Uplink Shared Channel (NPUSCH) format 2, to the signal processing system of the BS 101. In an embodiment, the plurality of uplink signals may be signals including control information. The NPUSCH format 2 is transmitted on one or more resource units and each of these resource units are repeated up several times to improve transmission reliability' and coverage without compromising on the low power and low complexity requirements of NB- loT applications. The signal processing system may process the plurality of the uplink signals in the NB-IoT physical layer received from each of the UEs 102 at an antenna of the BS 101. When the BS 101 receives the uplink signals, the signal processing system may perform channel estimation for the uplink signals and decode the uplink signals to recover original uplink control information. It may be worth noting that, the BS 101 implements block wise processing of the plurality of the uplink signals for channel estimation, and by considering CFO estimates obtained from current NPUSCH blocks and previous NPUSCH blocks using both DMRS and Data symbols, accuracy of estimation for a current processing block is improved. This allows the signal processing system to correctly and accurately decode the uplink signals even at lower SNR levels.

[0029] The signal processing system may be implemented in a variety of computing systems, such as, a server, a cloud computing system, a network server, a cloud-based server, and the like. In an embodiment, the signal processing system may be a dedicated server or may be a cloud-based server. The signal processing system of the present disclosure is communicably coupled to the plurality of UEs 102. Further, the signal processing sy stem may include a processor (not shown in FIG. 1), a I/O interface (not shown in FIG. 1), and the memory (not shown in FIG. 1). In some embodiments, the memory may be communicatively coupled to the processor. The memory stores instructions, executable by the processor, which, on execution, may cause the signal processing system to process the uplink signals, as disclosed in the present disclosure.

[0030] In an embodiment the communication network through which the BS 101 and the UEs

102 are connected may include, without limitation, a direct interconnection, Local Area Network (LAN), Wide Area Network (WAN), Controller Area Network (CAN), wireless network (e.g., using a Wireless Application Protocol), the Internet, and the like.

[0031] In operation, the BS 101 (also referred hereinafter as first network entity) may receive a first control message associated with a first communication block and a second control message associated with a second communication block from one of the UE 102 (UE 102a is referred as an illustration hereinafter for illustration). The UE 102a may also be referred to as a second network entity. In an example, the BS 101 may be in communication with the UE 102a via a communication channel (not shown).

[0032] In an embodiment, the BS 101 may extract at least one first control element and at least one second control element from the first communication block and the second communication block, respectively.

[0033] In an embodiment, the BS 101 may obtain one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element.

[0034] In an embodiment, the BS 101 may perform a weighted moving average of the one or more CFO estimates to generate a decision value. In an example, the BS 101 may determine a Log Likelihood Ratio (LLR) value associated with the generated decision value, wherein the generated decision value is an initial decision value. Thereafter, the BS 101 may compute a final decision value based on the LLR value.

[0035] In another embodiment, the BS 101 may determine a first Log Likelihood Ratio (LLR) value, which is associated with a first generated decision value pertaining to a first resource unit (RU). Further, the BS 101 may compute a first final LLR value pertaining to the first RU, based on the first LLR value. In an example, the BS 101 may compute the first final LLR value in-place memory pertaining to the first RU. Furthermore, the BS 101 may determine a second LLR value, which is associated with a second generated decision value pertaining to a second RU. Thereafter, the BS 101 may compute a second final LLR value pertaining to the second RU, based on the second LLR value. In an example, the BS 101 may compute the second final LLR value in-place memory pertaining to the second RU. For example, the first generated decision value and the second generated decision value may be corresponding initial decision values.

[0036] As per the above embodiment, the first final LLR value and the second final LLR value may be stored, in a memory' of the BS 101. Further, the BS 101 may compute a final decision value based on the stored first final LLR value and the stored second final LLR value. In an example, the final decision value may be stored in a common LLR output buffer associated with the BS 101. In an example embodiment, the BS 101 may perform averaging of the first final LLR value and the second final LLR value in order to compute the final decision value. The averaging of the first final LLR value and the second final LLR value may allow the BS 101 to accurately compute the final decision value which is representative of the final LLR value associated with the transmission of the control information of the respective UE 102 to the BS 101.

[0037] In an embodiment, the BS 101 may determine that a value of the estimated characteristics of the communication channel is below a predetermined threshold value. Thereafter, the BS 101 transmits to the UE 102, an RF signal with an optimized signal characteristics across the communication channel, based on the determination that the characteristics of the communication channel is below the predetermined threshold value. In an example, the RF signal comprises at least one of a control message and a data message.

[0038] In an alternate embodiment, the BS 101 may determine that a value of the estimated characteristics of the communication channel is above a predetermined threshold value. Thereafter, the BS 101 may transmit to the UE 102, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value. In an example, the RF signal comprises at least one of a control message and a data message. For example, the control message may comprise control information related to the respective UE 102. Similarly, the data message may be related to the respective UE 102 including user data payload.

[0039] In an embodiment, the BS 101 may determine that the decision value is above a frequency offset (FO) predetermined threshold. [0040] In an embodiment, the BS 101 may estimate, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the output value.

[0041] FIG. 2 illustrates a block diagram of the base station for performing channel estimation, in accordance with an embodiment of the present disclosure.

[0042] FIG. 2 is explained in conjunction with the BS 101 of FIG. 1. With reference to FIG. 2, there is shown a block representation of the BS 101.

[0043] In an embodiment, the BS 101 comprising a Central Processing Units 200 (also referred as "‘CPUs'’ or "one or more processors 200”), a memory 202, and Input/ Output (I/O) interface 204. The detailed description of the processor 200, the memory 202, and the I/O interface 204 is already mentioned under the description of FIG. 1, therefore, the same is not included herein for the sake of brevity⁷.

[0044] In an embodiment, the memory 202 may include data 206 and one or more modules 208. The one or more modules 208 may be configured to perform the steps of the present disclosure using the data 206, to perform channel estimation. In an embodiment, each of the one or more modules 208 may be a hardware unit which may be configured external to the memory 202 and coupled with the processor 200. As used herein, the term modules 208 refers to an Application Specific Integrated Circuit (ASIC), an electronic circuit, a Field- Programmable Gate Arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide described functionality. The one or more modules 208, when configured with the described functionality defined in the present disclosure, will result in a novel hardware.

[0045] In one implementation, the data 206 may include, for example, input data 210, a plurality⁷ of control elements 212, and a plurality of decision values. In one implementation, the modules 208 may include, for example, an input module 216, a control element extraction module 218, and a decision value generation module 220. It will be appreciated that such modules 208 may be represented as a single module or a combination of different modules.

[0046] In an embodiment, the input module 216 may be configured to receive input data 210 including a first control message associated with a first communication block and a second control message associated with a second communication block received from one of the UE 102.

[0047] In an embodiment, the control element extraction module 218 may be configured to extract at least one first control element and at least one second control element from the first communication block and the second communication block, respectively. In an example, the processor 200 may be configured to obtain one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element.

[0048] In an embodiment, the decision value generation module 220 may be configured to performing a weighted moving average of the one or more CFO estimates to generate a decision value. In an example, the processor 200 may be configured to determine that the decision value is above a frequency offset (FO) predetermined threshold. In an example, the processor 200 may be configured to estimate, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.

[0049] A person skilled in the art will appreciate that the processor 200 may be configured to perform the steps of the present disclosure using the data 206 instead of the one or more modules 208, to perform channel estimation.

[0050] A person skilled in the art will appreciate that any techniques other than the above- mentioned technique may be used to perform the steps performed by the input module 216, a control element extraction module 218, and a decision value generation module 220, which are configured to perform the channel estimation.

[0051] FIG. 3 shows an exemplary' flow chart illustrating method steps for performing channel estimation in the NB-IoT physical layer, in accordance with some embodiments of the present disclosure.

[0052] As illustrated in FIG. 3, the method 300 may comprise one or more steps. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

[0053] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

[0054] At step 302, a first control message associated with a first communication block and a second control message associated with a second communication block may be received at a first network entity and from a second network entity. In an example, the first network entity may be in communication with the second network entity via a communication channel. For example, the first network entity may be the BS 101 of FIG. 1 and from the second network entity may be one of the UEs 102 of FIG. 1. In another example, the first network entity' may be a distribution unit (DU) and the second network entity may be a Radio Frequency (RF)- enabled device. In a preferred embodiment, the second communication block may be received, at the first network entity and from the second network entity, upon receiving the first communication block. For example, the second communication block may sequentially follow the first communication block. In a preferred embodiment, the first communication block and the second communication block may be NB-IoT NPUSCH blocks.

[0055] At step 304, at least one first control element and at least one second control element may be extracted by the BS 101 from the first communication block and the second communication block, respectively. In an example, the at least one control element may include at least one of a Demodulation Reference Signal (DMRS) and one or more data symbols. In another example, the control message may include Uplink (UL) control information.

[0056] At step 306, one or more carrier frequency offset (CFO) estimates may be obtained by the BS 101 based on the at least one first control element and the at least one second control element. [0057] At step 308, a weighted moving average of the one or more CFO estimates may be performed by the BS 101 to generate a decision value.

[0058] In an embodiment, a Log Likelihood Ratio (LLR) value, associated with the generated decision value, may be determined by the BS 101. For example, the generated decision value may be an initial decision value. Further, the BS 101 may compute a final decision value based on the LLR value.

[0059] In another embodiment, a first Log Likelihood Ratio (LLR) value, which is associated with a first generated decision value pertaining to a first resource unit (RU), may be determined by the BS 101. Further, a first final LLR value pertaining to the first RU may be computed, based on the first LLR value. In an example, the first final LLR value may be computed in- place memory pertaining to the first RU. Furthermore, a second LLR value, which is associated with a second generated decision value pertaining to a second RU, may be determined. Thereafter, a second final LLR value pertaining to the second RU may be computed, based on the second LLR value. In an example, the second final LLR value may be computed in-place memory⁷ pertaining to the second RU. For example, the first generated decision value and the second generated decision value may be corresponding initial decision values.

[0060] As per the above embodiment, the first final LLR value and the second final LLR value may be stored, in a memory of the first network entity. Further, a final decision value may’ be computed based on the stored first final LLR value and the stored second final LLR value.

[0061] At step 310, the BS 101 may determine that the decision value is above a frequency offset (FO) predetermined threshold.

[0062] At step 312, the BS 101 may estimate, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.

[0063] In an embodiment, the BS 101 determines that a value of the estimated characteristics of the communication channel is below a predetermined threshold value. Thereafter, the BS 101 transmits to the UE 102, an RF signal with an optimized signal characteristics across the communication channel, based on the determination that the characteristics of the communication channel is below the predetermined threshold value. In an example, the RF signal comprises at least one of a control message and a data message.

[0064] In an alternate embodiment, the BS 101 may determine that a value of the estimated characteristics of the communication channel is above a predetermined threshold value. Thereafter, the BS 101 may transmit to the UE 102, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

[0065] FIG. 4 illustrates an embodiment of a device 400 wherein the method for performing channel estimation in the NB-IoT physical layer may be implemented, according to the embodiments as disclosed herein. It will be appreciated that the device 400 is associated with the BS 101. As shown in FIG. 4, the device 400 comprises a processor 410, a memory' 420, a storage component 430, an input component 440, an output component 450, a communication interface 460, and a bus 470.

[0066] The processor 410, as used herein, means any type of computational circuit that may comprise hardware elements and software elements. The processor 410 may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and/or one or more single core processors, a distributed processing system, or the like. The processor 410 may be a Central Processing Unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), an application-specific integrated circuit (ASIC), or another type of processing component.

[0067] Memory 420 includes a non-transitory computer readable medium. Memory 420 includes a random-access memory' (RAM), a read only memoiy (ROM), and/or another ty pe of dynamic or static storage device (e.g., a flash memory, a magnetic memory, and/or an optical memory) that stores information and/or instructions for use by processor 410. The memoiy 420 comprises machine-readable instructions which are executable by the processor 410. These machine-readable instructions when executed by the processor 410 cause the processor 410 to perform one or more method steps of an embodiment described above. [0068] Storage component 430 stores information and/or software related to the operation and use of the device 400. For example, storage component 430 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optic disk, and/or a solid-state disk), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and/or another type of non-transitory computer-readable medium, along with a corresponding drive.

[0069] Input component 440 is configured to receive information, such as user input. For example, the input component 440 may include, but not be limited to, a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and/or a microphone. Additionally, or alternatively, the input component 440 may include a sensor for sensing information (e.g., a global positioning system (GPS), an accelerometer, a gyroscope, and/or an actuator).

[0070] Output component 450 is configured to provide output information from the device 400. For example, the output component 450 may be, but not limited to, a display, a speaker, instructions to an external device, and/or one or more light-emitting diodes (LEDs).

[0071] Communication interface 460 is an interface that provides a communication connection to other devices, such as external devices and internal devices. The connection by the communication interface 460 can be a wired connection, a wireless connection, or a combination of wired and wireless connections, and can be a direct connection or an indirect connection via a communication network that exists between the device 400 and other devices. In other words, the standard of the communication interface 460 is not limited.

[0072] The bus 470 acts as an interconnect between the processor 410, the memory 420, the storage component 430, the input component 440, the output component 450, and the communication interface 460 of the device 400. The bus 470 may include a wired interconnection or a wireless interconnection.

[0073] The number and arrangement of components shown in FIG. 4 are provided as an example. In practice, device 400 may include additional components, fewer components, different components, or differently arranged components than those shown in FIG. 4. Additionally, or alternatively, a set of components (e.g., one or more components) of device 400 may perform one or more functions described as being performed by another set of components of device 400. Further, one or more method steps described in any of the embodiments may be performed utilizing a plurality of devices 400 in communication with one another.

[0074] In an embodiment [1], a method comprising: receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extracting at least one first control element and at least one second control element from the first communication block and the second communication block, respectively; obtaining one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; performing a weighted moving average of the one or more CFO estimates to generate a decision value; determining that the decision value is above a frequency offset (FO) predetermined threshold; and estimating, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.

[0075] In an embodiment [2], the method, described in the embodiment [1], further comprises: determining a Log Likelihood Ratio (LLR) value associated with the generated decision value, wherein the generated decision value is an initial decision value; and computing a final decision value based on the LLR value.

[0076] In an embodiment [3], the method, described in the embodiment [1], further comprises: determining a first Log Likelihood Ratio (LLR) value associated with a first generated decision value pertaining to a first resource unit (RU); computing, based on the first LLR value, a first final LLR value pertaining to the first RU; determining a second LLR value associated with a second generated decision value pertaining to a second RU; computing, based on the second LLR value, a second final LLR value pertaining to the second RU, wherein the first generated decision value and the second generated decision value are corresponding initial decision values; storing, in a memory of the first netw ork entity, the first final LLR value and the second final LLR value; and computing a final decision value based on the stored first final LLR value and the stored second final LLR value.

[0077] In an embodiment [4], the method, described in the embodiment [1], further comprises: determining that a value of the estimated characteristics of the communication channel is below a predetermined threshold value; and transmitting, by the first network entity and to the second network entity, an RF signal with an optimized signal characteristics across the communication channel, based on the determination that the characteristics of the communication channel is below the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

[0078] In an embodiment [5], the method, described in the embodiment [1], further comprises: determining that a value of the estimated characteristics of the communication channel is above a predetermined threshold value; and transmitting, by the first network entity and to a second network entity, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

[0079] In an embodiment [6], in the method described in the embodiment [1], the at least one control element comprises at least one of a Demodulation Reference Signal (DMRS) and one or more data symbols.

[0080] In an embodiment [7], in the method described in the embodiment [1], the first network entity is a distribution unit (DU) and the second network entity is a Radio Frequency (RF)- enabled device.

[0081] In an embodiment [8], in the method described in the embodiment [1], the second communication block is received, at the first network entity and from the second network entity, upon receiving the first communication block.

[0082] In an embodiment [9], in the method described in the embodiment [1], the first communication block and the second communication block are Narrowband-Intemet-of- Things (NB-IoT) Narrowband Physical Uplink Shared Channel (NPUSCH) blocks.

[0083] In an embodiment [10], an apparatus is configured to: receive, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extract at least one first control element and at least one second control element from the first communication block and the second communication block, respectively; obtain one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; perform a weighted moving average of the one or more CFO estimates to generate a decision value: determine that the decision value is above a frequency offset (FO) predetermined threshold; and estimate, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the output value.

[0084] In an embodiment [11], the apparatus, described in the embodiment [10], is further configured to: detennine a Log Likelihood Ratio (LLR) value associated with the generated decision value, wherein the generated decision value is an initial decision value; and compute a final decision value based on the LLR value.

[0085] In an embodiment [12], the apparatus, described in the embodiment [10], is further configured to: determine a first Log Likelihood Ratio (LLR) value associated with a first generated decision value pertaining to a first resource unit (RU); compute, based on the first LLR value, a first final LLR value pertaining to the first RU; determine a second LLR value associated with a second generated decision value pertaining to a second RU; compute, based on the second LLR value, a second final LLR value pertaining to the second RU, wherein the first generated decision value and the second generated decision value are corresponding initial decision values; store, in a memory⁷ of the first network entity⁷, the first final LLR value and the second final LLR value; and compute a final decision value based on the stored first final LLR value and the stored second final LLR value.

[0086] In an embodiment [13], the apparatus, described in the embodiment [10], is further configured to: determine a value of the estimated characteristics of the communication channel is below a predetermined threshold value; and transmit, by⁷ the first network entity⁷ and to the second network entity⁷, an RF signal with an optimized signal characteristics across the communication channel, based on the determination that the characteristics of the communication channel is below the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

[0087] In an embodiment [14], the apparatus, described in the embodiment [10], is further configured to: determine that a value of the estimated characteristics of the communication channel is above a predetermined threshold value; and transmit, by the first network entity and to a second network entity, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

[0088] In an embodiment [15], in the apparatus described in the embodiment [10]. the at least one control element comprises at least one of a Demodulation Reference Signal (DMRS) and one or more data symbols.

[0089] In an embodiment [16], in the apparatus described in the embodiment [10], the control message comprises Uplink (UL) control information.

[0090] In an embodiment [17], in the apparatus described in the embodiment [10], the first network entity is a distribution unit (DU) and the second network entity is a Radio Frequency (RF)-enabled device.

[0091] In an embodiment [18], in the apparatus described in the embodiment [10], the second communication block is received, at the first network entity and from the second network entity, upon receiving the first communication block.

[0092] In an embodiment [19], in the apparatus described in the embodiment [10], the first communication block and the second communication block are N arrowban d-Intemet-of- Things (NB-IoT) Narrowband Physical Uplink Shared Channel (NPUSCH) blocks.

[0093] In an embodiment [20], a non-transitory computer-readable medium having program instructions stored thereon, executed by an apparatus for wireless communication, is disclosed. The program instructions may comprise: receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extracting at least one first control element and at least one second control element from the first communication block and the second communication block, respectively; obtaining one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; performing a weighted moving average of the one or more CFO estimates to generate a decision value; determining that the decision value is above a frequency offset (FO) predetermined threshold; and estimating, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.

[0094] In a non-limiting embodiment of the present disclosure, one or more non-transitory computer-readable media may be utilized for implementing the embodiments consistent with the present disclosure. A computer-readable medium refers to any type of physical memory (such as the memory 610) on which information or data readable by a processor may be stored. Thus, a computer-readable media may store one or more instructions for execution by the at least one processor 608. including instructions for causing the at least one processor 608 to perform steps or stages consistent with the embodiments described herein. The term “computer-readable media” should be understood to include tangible items and exclude carrier waves and transient signals. By way of example, and not limitation, such computer-readable media can comprise Random Access Memory (RAM), Read-Only Memoiy (ROM), volatile memory, non-volatile memory’, hard drives, Compact Disc (CD) ROMs, Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media.

[0095] Thus, certain aspects may comprise a computer program product for performing the operations presented herein. For example, such a computer program product may comprise a computer readable media having instructions stored (and/or encoded) thereon, the instructions being executable by one or more processors to perform the operations described herein. For certain aspects, the computer program product may include packaging material.

[0096] The various illustrative logical blocks, modules, and operations described in connection with the present disclosure may be implemented or performed with a general-purpose processor, discrete gate or transistor logic, discrete hardw are components or any combination thereof designed to perform the functions described herein. A general-purpose processor may include a microprocessor, but in the alternative, the processor may include any commercially available processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e g., a plurality of microprocessors, or any other such configuration. [0097] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the scope of the embodiments as described herein.

Claims

We Claim:

1. A method comprising: receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extracting at least one first control element and at least one second control element from the first communication block and the second communication block, respectively ; obtaining one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; performing a weighted moving average of the one or more CFO estimates to generate a decision value; determining that the decision value is above a frequency offset (FO) predetermined threshold; and estimating, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.

2. The method as claimed in claim 1, wherein the method further comprises: determining a Log Likelihood Ratio (LLR) value associated with the generated decision value, wherein the generated decision value is an initial decision value; and computing a final decision value based on the LLR value.

3. The method as claimed in claim 1, wherein the method further comprises: determining a first Log Likelihood Ratio (LLR) value associated with a first generated decision value pertaining to a first resource unit (RU); computing, based on the first LLR value, a first final LLR value pertaining to the first

RU; determining a second LLR value associated with a second generated decision value pertaining to a second RU; computing, based on the second LLR value, a second final LLR value pertaining to the second RU, wherein the first generated decision value and the second generated decision value are corresponding initial decision values; storing, in a memory of the first network entity, the first final LLR value and the second final LLR value; and computing a final decision value based on the stored first final LLR value and the stored second final LLR value.

4. The method as claimed in claim 1, wherein the method further comprises: determining that a value of the estimated characteristics of the communication channel is below a predetermined threshold value; and transmitting, by the first network entity and to the second network entity, an RF signal with an optimized signal characteristics across the communication channel, based on the detemiination that the characteristics of the communication channel is below the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

5. The method as claimed in claim 1, wherein the method further comprises: determining that a value of the estimated characteristics of the communication channel is above a predetermined threshold value; and transmiting, by the first network entity and to a second network entity, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

6. The method as claimed in claim 1, wherein the at least one control element comprises at least one of a Demodulation Reference Signal (DMRS) and one or more data symbols.

7. The method as claimed in claim 1, wherein the first network entity is a distribution unit (DU) and the second network entity is a Radio Frequency (RF)-enabled device.

8. The method as claimed in claim 1, wherein the second communication block is received, at the first network entity and from the second netw ork entity, upon receiving the first communication block.

9. The method as claimed in claim 1, wherein the first communication block and the second communication block are Narrowband-Intemet-of-Things (NB-IoT) Narrowband Physical Uplink Shared Channel (NPUSCH) blocks.

10. An apparatus configured to: receive, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extract at least one first control element and at least one second control element from the first communication block and the second communication block, respectively; obtain one or more earner frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; perform a weighted moving average of the one or more CFO estimates to generate a decision value; determine that the decision value is above a frequency offset (FO) predetermined threshold; and estimate, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the output value.

11. The apparatus as claimed in claim 10, wherein the apparatus is further configured to: determine a Log Likelihood Ratio (LLR) value associated with the generated decision value, wherein the generated decision value is an initial decision value; and compute a final decision value based on the LLR value.

12. The apparatus as claimed in claim 10, wherein the apparatus is further configured to: determine a first Log Likelihood Ratio (LLR) value associated with a first generated decision value pertaining to a first resource unit (RU); compute, based on the first LLR value, a first final LLR value pertaining to the first RU; determine a second LLR value associated with a second generated decision value pertaining to a second RU; compute, based on the second LLR value, a second final LLR value pertaining to the second RU, wherein the first generated decision value and the second generated decision value are corresponding initial decision values; store, in a memory of the first network entity, the first final LLR value and the second final LLR value; and compute a final decision value based on the stored first final LLR value and the stored second final LLR value.

13. The apparatus as claimed in claim 10, wherein the apparatus is further configured to: determine a value of the estimated characteristics of the communication channel is below a predetermined threshold value; and transmit, by the first network entity and to the second network entity, an RF signal with an optimized signal characteristics across the communication channel, based on the determination that the characteristics of the communication channel is below the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

14. The apparatus as claimed in claim 10, wherein the apparatus is further configured: determine that a value of the estimated characteristics of the communication channel is above a predetermined threshold value; and transmit, by the first network entity and to a second network entity, an RF signal with an optimized signal strength across the communication channel, based on the determination that the characteristics of the communication channel is above the predetermined threshold value, wherein the RF signal comprises at least one of a control message and a data message.

15. The apparatus as claimed in claim 10, wherein the at least one control element comprises at least one of a Demodulation Reference Signal (DMRS) and one or more data symbols.

16. The apparatus as claimed in claim 10, wherein the control message comprises Uplink (UL) control information.

17. The apparatus as claimed in claim 10, wherein the first network entity is a distribution unit (DU) and the second network entity is a Radio Frequency (RF)-enabled device.

18. The apparatus as claimed in claim 10, wherein the second communication block is received, at the first network entity and from the second network entity, upon receiving the first communication block.

19. The apparatus as claimed in claim 10, wherein the first communication block and the second communication block are Narrowband-Intemet-of-Things (NB-IoT) Narrowband Physical Uplink Shared Channel (NPUSCH) blocks.

20. A non-transitory computer-readable medium having program instructions stored thereon, executed by an apparatus for wireless communication, wherein the program instructions may comprise: receiving, at a first network entity and from a second network entity, a first control message associated with a first communication block and a second control message associated with a second communication block, wherein the first network entity is in communication with the second network entity via a communication channel; extracting at least one first control element and at least one second control element from the first communication block and the second communication block, respectively; obtaining one or more carrier frequency offset (CFO) estimates based on the at least one first control element and the at least one second control element; performing a weighted moving average of the one or more CFO estimates to generate a decision value; determining that the decision value is above a frequency offset (FO) predetermined threshold; and estimating, based on the determining that the decision value is above the FO predetermined threshold, characteristics of the communication channel based on the decision value.