LDPC decoding using mean value and offset associated with a confidence level value

Abstract

Various aspects of this disclosure relate generally to wireless communication. In some aspects, a wireless communication device can receive transmissions associated with one or more bits. The wireless communication device can decode the transmissions using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of one or more confidence level values ​​and an offset at least in part based on the number of one or more confidence level values. Numerous other aspects are described.

Description

Cross-reference to related applications

[0001] This patent application claims priority to U.S. Patent Application No. 18 / 545,373, filed December 19, 2023, entitled "DECODING USING AVERAGE AND OFFSET ASSOCIATED WITH CONFIDENCE LEVEL VALUES," which is assigned to the assignee of this application. The disclosure of the earlier application is considered part of this patent application and is incorporated herein by reference. Technical Field

[0002] All aspects of this disclosure relate to wireless communication in general, and more particularly to techniques, apparatus and methods for decoding using an average value and an offset associated with a confidence level value. Background Technology

[0003] Wireless communication systems are widely deployed to provide a variety of services, including voice, text, messaging, video, data, and / or other services. Services may include unicast, multicast, and / or broadcast services, etc. Typical wireless communication systems employ multiple access radio access technologies (RATs) capable of supporting communication with multiple users by sharing available system resources (e.g., time-domain resources, frequency-domain resources, spatial-domain resources, and / or device transmit power, etc.). Examples of such multiple access RATs include Code Division Multiple Access (CDMA) systems, Time Division Multiple Access (TDMA) systems, Frequency Division Multiple Access (FDMA) systems, Orthogonal Frequency Division Multiple Access (OFDMA) systems, Single-Carrier Frequency Division Multiple Access (SC-FDMA) systems, and Time Division Synchronous Code Division Multiple Access (TD-SCDMA) systems.

[0004] The aforementioned Multiple Access RATs have been adopted in various telecommunications standards to provide a common protocol enabling different wireless communication devices to communicate at the city, national, regional, or global level. An example telecommunications standard is New Radio (NR). NR (also known as 5G) is part of the continuous evolution of mobile broadband announced by the 3rd Generation Partnership Project (3GPP). NR (and other mobile broadband evolutions beyond NR) can be designed to better support the Internet of Things (IoT) and reduced-capacity device deployments, industrial connectivity, millimeter-wave (mmWave) expansion, licensed and unlicensed spectrum access, non-terrestrial network (NTN) deployments, sidelinks and other device-to-device direct communication technologies (e.g., cellular vehicle-to-everything (CV2X) communications), massive MIMO, decomposed network architectures and network topology expansion, multi-subscriber implementations, high-precision positioning and / or radio frequency (RF) sensing, and more. As the demand for mobile broadband access continues to grow, further improvements to NR can be implemented, and other radio access technologies (such as 6G) can be introduced to further advance mobile broadband evolution. Summary of the Invention

[0005] Some aspects described herein relate to an apparatus for performing wireless communication at a wireless communication device. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured individually or collectively to receive a transmission associated with one or more bits. The one or more processors may be configured individually or collectively to decode the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to a number of the one or more confidence level values ​​and an offset at least in part based on that number of the one or more confidence level values.

[0006] Some aspects described herein relate to a method of wireless communication performed by a wireless communication device. The method may include receiving a transmission associated with one or more bits. The method may include decoding the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to a number of the one or more confidence level values ​​and an offset at least in part based on that number of the one or more confidence level values.

[0007] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions for wireless communication by a wireless communication device. When executed by one or more processors of the wireless communication device, the set of instructions enables the wireless communication device to receive a transmission associated with one or more bits. When executed by one or more processors of the wireless communication device, the set of instructions enables the wireless communication device to decode the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of the one or more confidence level values ​​and an offset at least in part based on that number of the one or more confidence level values.

[0008] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for receiving a transmission associated with one or more bits. The apparatus may also include components for decoding the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to a number of the one or more confidence level values, and at least in part based on an offset from that number of the one or more confidence level values.

[0009] Various aspects of this disclosure may be implemented or be implemented as described in whole by or embodied in the methods, apparatus, systems, computer program products, non-transitory computer-readable media, user equipment, base stations, network nodes, network entities, wireless communication devices and / or processing systems as fully described in the specification and drawings and illustrated in the specification and drawings.

[0010] The preceding paragraphs of this section have broadly summarized some aspects of this disclosure. These and additional aspects and their associated advantages will be described below. The disclosed aspects can serve as the basis for modifying or designing other aspects for performing the same or similar purposes of this disclosure. Such equivalent aspects do not depart from the scope of the appended claims. The characteristics of the aspects disclosed herein, their organization and operation, and their associated advantages will be better understood from the following description taken in conjunction with the accompanying drawings. Attached Figure Description

[0011] The accompanying drawings illustrate some aspects of this disclosure but do not limit its scope, as other aspects can be achieved by this description. Each drawing in the drawings is provided for illustrative and descriptive purposes and not as a definition of limitation of the claims. Identical or similar reference numerals in different drawings may identify identical or similar elements.

[0012] Figure 1 This is a diagram illustrating an example of a wireless communication network according to the present disclosure.

[0013] Figure 2This is a diagram illustrating an example network node communicating with an example user equipment (UE) in a wireless network according to the present disclosure.

[0014] Figure 3 This is a diagram illustrating an example decomposed base station architecture according to this disclosure.

[0015] Figure 4 This is an illustration of an example of a low-density parity-check (LDPC) code according to the present disclosure.

[0016] Figure 5 This is a diagram illustrating an example of confidence propagation decoding according to this disclosure.

[0017] Figure 6 This is a diagram illustrating an example of the min-sum approximation according to this disclosure.

[0018] Figure 7 This is a diagram illustrating an example of a mathematical function according to this disclosure.

[0019] Figure 8 This is a diagram illustrating an example of operations associated with a verification node according to this disclosure.

[0020] Figure 9 This is a diagram illustrating an example of a lookup table according to this disclosure.

[0021] Figures 10A to 10D This is a diagram illustrating an example of simulation results involving a dominant decoder according to this disclosure.

[0022] Figure 11A and Figure 11B This is a diagram illustrating an example of simulation results involving a dynamic offset min-sum (DOMS) decoder according to this disclosure.

[0023] Figure 12 This is a diagram illustrating an example process performed, for example, at a wireless communication device or an apparatus of a wireless communication device, according to the present disclosure.

[0024] Figure 13 This is a diagram of an example device for wireless communication according to the present disclosure.

[0025] Figure 14 This is a diagram of an example device for wireless communication according to the present disclosure. Detailed Implementation

[0026] Various aspects of this disclosure are described below with reference to the accompanying drawings. However, aspects of this disclosure may be embodied in many different forms and should not be construed as limited to any specific aspect illustrated or described with reference to the drawings or otherwise presented in this disclosure. Rather, these aspects are provided so that this disclosure will be comprehensive and complete, and will fully convey the scope of this disclosure to those skilled in the art. Those skilled in the art will understand that the scope of this disclosure is intended to cover any aspect of this disclosure disclosed herein, whether implemented independently of or in combination with any other aspect of this disclosure. For example, various combinations or numbers of aspects set forth herein may be used to implement an apparatus or a method of practice. Furthermore, the scope of this disclosure is intended to cover apparatuses having structures and / or functionalities other than those available for practicing the various aspects of this disclosure set forth herein, or methods of practice using those other structures and / or functionalities. Any aspect of this disclosure disclosed herein may be embodied by one or more elements of the claims.

[0027] Various methods, operations, apparatuses, and techniques will now be presented with reference to them. These methods, operations, apparatuses, and techniques will be described in detail below and illustrated in the accompanying drawings by various boxes, modules, components, circuits, steps, processes, or algorithms (collectively, “elements”). These elements may be implemented using hardware, software, or a combination of hardware and software. Whether such elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the system as a whole.

[0028] In wireless networks, low-density parity-check (LDPC) decoding is a technique that can be used in error-correcting codes, particularly in the context of forward error correction (FEC). LDPC decoding can utilize computationally intensive parity node kernels. The minimum sum approximation It can reduce hardware constraints. However, the min-sum approximation performs poorly when a term is not dominant. Therefore, in many cases, the min-sum approximation may result in a significant loss of error correction capability.

[0029] Various aspects are involved in the overall LDPC decoder. Some aspects are more specifically involved in the dominant decoder, such as... (in It is a group (size or quantity), which is dominant. The operation is performed on the item. In some aspects, the wireless communication device can receive and decode a transmission associated with one or more bits. The wireless communication device can decode the transmission using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and an offset based at least in part on the number of one or more confidence level values. For example, the average could be... And the offset can be In some examples, the dominant decoder can identify the difference threshold of minterms. Any item within (e.g., satisfying) Any item of which In some cases, This means that each of one or more confidence level values ​​is equal to the minimum confidence level value.

[0030] Specific aspects of the subject matter described in this disclosure can be implemented to achieve one or more of the following potential advantages. In some examples, by decoding the transmission using the average and offset of one or more confidence level values, the described techniques can be used to improve error correction performance so that the decoding result is closer to confidence propagation, while preserving the hardware-friendly implementation of the min-sum approximation. For example, the dominant decoder can bridge the gap in the check node kernel. Approximate with min-sum The difference in error correction performance between them. For example, a dominant decoder can provide significant gains in error correction performance and convergence speed, resulting in fewer cycles, reduced power consumption, and faster results. In such cases, the dominant decoder can provide minimal increase in complexity without introducing problems involving finite precision. For example, the DOMS decoder can provide significant improvements from a performance perspective.

[0031] Multiple access radio access technology (RAT) has been adopted in various telecommunications standards to provide a common protocol that enables wireless communication devices to communicate at the city, enterprise, national, regional, or global level. For example, 5G New Radio (NR) is part of the continuous mobile broadband evolution announced by the 3rd Generation Partnership Project (3GPP). 5G NR supports a variety of technologies and use cases, including enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), massive machine-type communication (mMTC), millimeter wave (mmWave) technology, beamforming, network slicing, edge computing, Internet of Things (IoT) connectivity and management, and network function virtualization (NFV).

[0032] With increasing demand for broadband access and the evolution of technologies supported by wireless communication networks, further technological improvements can be adopted in or implemented for 5G NR or future RATs (such as 6G) to further advance the evolution of wireless communication for a variety of existing and new use cases and applications. These technological improvements can be associated with new frequency band extensions, licensed and unlicensed spectrum access, overlapping spectrum use, small cell deployments, non-terrestrial network (NTN) deployments, decomposed network architectures and network topology extensions, device aggregation, advanced duplex communication, sidelinks and other device-to-device direct communication, IoT (including passive or ambient IoT) networks, reduced-capacity (RedCap) UE functionality, industrial connectivity, multi-subscriber implementations, high-precision positioning, radio frequency (RF) sensing and / or artificial intelligence or machine learning (AI / ML), and more. Such technological improvements can support use cases such as wireless backhaul, wireless data centers, extended reality (XR) and metaverse applications, meta-services for supporting vehicle connectivity, holographic and mixed reality communications, autonomous and collaborative robots, vehicle platooning and collaborative manipulation, sensor networks, posture monitoring, brain-computer interfaces, digital twin applications, asset management, and general coverage applications using off-ground and / or aerial platforms, etc. The methods, operations, apparatuses, and techniques described herein can implement one or more of the foregoing technologies and / or support one or more of the foregoing use cases.

[0033] Figure 1 This is a diagram illustrating an example of a wireless communication network 100 according to the present disclosure. The wireless communication network 100 may be a 5G (or NR) network or a 6G network, or may include elements of a 5G (or NR) network or elements of a 6G network, etc. The wireless communication network 100 may include a plurality of network nodes 110, shown as network node (NN) 110a, network node 110b, network node 110c, and network node 110d. Network nodes 110 may support communication with a plurality of UEs 120 (shown as UE120a, UE 120b, UE 120c, UE 120d, and UE 120e).

[0034] Network nodes 110 and UEs 120 of wireless communication network 100 can communicate using the electromagnetic spectrum, which can be subdivided into various categories, bands, carriers, and / or channels according to frequency or wavelength. For example, devices of wireless communication network 100 can communicate using one or more operating bands. In some aspects, multiple wireless communication networks 100 can be deployed in a given geographical area. Each wireless communication network 100 can support a specific radio access technology (RAT) (which may also be referred to as an air interface) and can operate on one or more carrier frequencies in one or more frequency ranges. Examples of RATs include 4G RAT, 5G / NR RAT, and / or 6G RAT, etc. In some examples, when multiple RATs are deployed in a given geographical area, each RAT in that geographical area can operate on a different frequency to avoid interference with each other.

[0035] Various operating bands have been defined by frequency range designations: FR1 (410 MHz to 7.125 GHz), FR2 (24.25 GHz to 52.6 GHz), FR3 (7.125 GHz to 24.25 GHz), FR4a or FR4-1 (52.6 GHz to 71 GHz), FR4 (52.6 GHz to 114.25 GHz), and FR5 (114.25 GHz to 300 GHz). Although a portion of FR1 is greater than 6 GHz, in some documents and articles, FR1 is often (interchangeably) referred to as the “sub-6 GHz” band. Similarly, in some documents and articles, FR2 is often (interchangeably) referred to as the “millimeter wave” band, but this is distinct from the Extremely High Frequency (EHF) band (30 GHz to 300 GHz) designated as the “millimeter wave” band by the International Telecommunication Union (ITU). The frequencies between FR1 and FR2 are generally referred to as the midband frequencies, including FR3. Frequency bands falling within FR3 can inherit FR1 or FR2 characteristics, thereby effectively extending the characteristics of FR1 or FR2 into midband frequencies. Therefore, "below 6 GHz" (if used herein) can broadly refer to frequencies less than 6 GHz that are within FR1 and / or included in midband frequencies. Similarly, the term "millimeter wave" (if used herein) can broadly refer to frequencies included in midband frequencies, within FR2, FR4, FR4-a, FR4-1, or FR5, and / or within the EHF band. Higher frequency bands can extend 5G NR operation, 6G operation, and / or other RATs above 52.6 GHz. For example, each of FR4a, FR4-1, FR4, and FR5 falls within the EHF band. In some examples, wireless communication network 100 can implement dynamic spectrum sharing (DSS), where multiple RATs (e.g., 4G / LTE and 5G / NR) are implemented within a single frequency band using dynamic bandwidth allocation (e.g., based on user demand). It is conceivable that the frequencies included in these operating bands (e.g., FR1, FR2, FR3, FR4, FR4-a, FR4-1 and / or FR5) can be modified, and the techniques described herein are applicable to those modified frequency ranges.

[0036] Network node 110 may include one or more devices, components, or systems that enable communication between UE 120 and one or more devices, components, or systems of wireless communication network 100. Network node 110 may be, may include, or may also be referred to as an NR network node, 5G network node, 6G network node, node B, eNB, gNB, access point (AP), transmit / receive point (TRP), mobility element, core, network entity, network element, network equipment, and / or another type of device, component, or system included in a radio access network (RAN).

[0037] Network node 110 may be implemented as a single physical node (e.g., a single physical structure) or as two or more physical nodes (e.g., two or more different physical structures). For example, network node 110 may be a device or system implementing a portion of a radio protocol stack, a device or system implementing a complete radio protocol stack (such as a complete gNB protocol stack), or a collection of devices or systems collectively implementing a complete radio protocol stack. For example, and as shown, network node 110 may be an aggregated network node (with an aggregated architecture), meaning that network node 110 can implement a complete radio protocol stack physically and logically integrated within a single node (e.g., a single physical structure) in the wireless communication network 100. For example, aggregated network node 110 may consist of a single standalone base station or a single TRP that uses the complete radio protocol stack to implement or facilitate communication between UE 120 and the core network of wireless communication network 100.

[0038] Alternatively, and also as shown in the figure, network node 110 can be a decomposed network node (sometimes referred to as a decomposed base station), meaning that network node 110 can realize a radio protocol stack that is physically distributed and / or logically distributed among two or more nodes in the same or different geographic locations. For example, a decomposed network node may have a decomposed architecture. In some deployments, decomposed network node 110 may be used in integrated access and backhaul (IAB) networks, in open radio access networks (O-RAN) (such as network configurations compliant with the O-RAN Alliance), or in virtualized radio access networks (vRAN) (also referred to as cloud radio access networks (C-RAN)) to facilitate scaling by decomposing base station functionality into multiple units that can be deployed independently.

[0039] Network nodes 110 of the wireless communication network 100 may include one or more central units (CUs), one or more distributed units (DUs), and / or one or more radio units (RUs). CUs may host one or more higher-layer control functions, such as Radio Resource Control (RRC) functions, Packet Data Convergence Protocol (PDCP) functions, and / or Service Data Adaptation Protocol (SDAP) functions, etc. DUs may host one or more of the Radio Link Control (RLC) layer, Media Access Control (MAC) layer, and / or one or more higher physical (PHY) layers, at least in part, according to functional splits (such as functional splits defined by 3GPP). In some examples, DUs may also host one or more lower PHY layer functions, such as Fast Fourier Transform (FFT), Inverse FFT (iFFT), beamforming, Physical Random Access Channel (PRACH) extraction and filtering, and / or scheduling of resources for one or more UEs 120, etc. RUs may host RF processing functions or lower PHY layer functions, such as FFT, iFFT, beamforming, or PRACH extraction and filtering, etc., according to functional splits (such as lower-layer functional splits). In this type of architecture, each RU can be operated to handle over-the-air (OTA) communications with one or more UE 120s.

[0040] In some aspects, a single network node 110 may include a combination of one or more CUs, one or more DUs, and / or one or more RUs. Additionally or alternatively, network node 110 may include one or more near real-time (near RT) RAN Intelligent Controllers (RICs) and / or one or more non-real-time (non-RT) RICs. In some examples, CUs, DUs, and / or RUs may be implemented as virtual units, such as Virtual Central Units (VCUs), Virtual Distributed Units (VDUs), or Virtual Radio Units (VRUs), etc. Virtual units may be implemented as virtual network functions, such as those associated with cloud deployments.

[0041] Some network nodes 110 (e.g., base stations, RUs, or TRPs) can provide communication coverage for specific geographic areas. In 3GPP, the term "cell" can refer to the coverage area of ​​network node 110 or to network node 110 itself, depending on the context in which the term is used. Network node 110 can support one or more (e.g., three) cells. In some examples, network node 110 can provide communication coverage for macro cells, pico cells, femto cells, or another type of cell. A macro cell can cover a relatively large geographic area (e.g., a radius of several kilometers) and can allow unrestricted access by UE 120 with a service subscription. A pico cell can cover a relatively small geographic area and can allow unrestricted access by UE 120 with a service subscription. A femto cell can cover a relatively small geographic area (e.g., a residential area) and can allow restricted access by UE 120 associated with that femto cell (e.g., UE 120 in a Closed Subscriber Group (CSG)). The network node 110 used for a macro cell may be referred to as a macro network node. Network node 110 used for a picocell may be referred to as a pico network node. Network node 110 used for a femtocell may be referred to as a femto network node or a home network node. In some examples, the cell may not necessarily be stationary. For example, the geographical area of ​​the cell may be mobile based on the location of the associated mobile network node 110 (e.g., a train, satellite base station, unmanned aerial vehicle, or non-terrestrial network (NTN) network node).

[0042] The wireless communication network 100 can be a heterogeneous network, comprising different types of network nodes 110, such as macro network nodes, piconet nodes, femtonet nodes, relay network nodes, aggregation network nodes, and / or decomposition network nodes, etc. Figure 1 In the example shown, network node 110a can be a macro network node for macro cell 130a, network node 110b can be a pico network node for pico cell 130b, and network node 110c can be a femto network node for femto cell 130c. Compared to other types of network nodes 110, the various types of network nodes 110 typically transmit at different power levels, serve different coverage areas, and / or have different effects on interference in the wireless communication network 100. For example, macro network nodes may have high transmit power levels (e.g., 5 watts to 40 watts), while pico network nodes, femto network nodes, and relay network nodes may have lower transmit power levels (e.g., 0.1 watts to 2 watts).

[0043] In some examples, network node 110 may be, may include, or operate as a RU, TRP, or base station communicating with one or more UEs 120 via a radio access link (which may be referred to as a "Uu" link). The radio access link may include a downlink and an uplink. A "downlink" (or "DL") refers to the communication direction from network node 110 to UE 120, and an "uplink" (or "UL") refers to the communication direction from UE 120 to network node 110. Downlink channels may include one or more control channels and one or more data channels. Downlink control channels may be used to transmit downlink control information (DCI) (e.g., scheduling information, reference signals, and / or configuration information) from network node 110 to UE 120. Downlink data channels may be used to transmit downlink data (e.g., user data associated with UE 120) from network node 110 to UE 120. Downlink control channels may include one or more physical downlink control channels (PDCCH), and downlink data channels may include one or more physical downlink shared channels (PDSCH). The uplink channel may similarly include one or more control channels and one or more data channels. The uplink control channel can be used to transmit uplink control information (UCI) from UE 120 to network node 110 (e.g., transmitting corresponding reference signals and / or feedback with one or more downlinks). The uplink data channel can be used to transmit uplink data (e.g., user data associated with UE 120) from UE 120 to network node 110. The uplink control channel may include one or more physical uplink control channels (PUCCH), and the uplink data channel may include one or more physical uplink shared channels (PUSCH). The downlink and uplink may each include a set of resources on which network node 110 and UE 120 can communicate.

[0044] Downlink and uplink resources may include time-domain resources (frames, subframes, time slots, and / or symbols), frequency-domain resources (bands, component carriers, subcarriers, resource blocks, and / or resource elements), and / or spatial-domain resources (specific transmission directions and / or beam parameters). Frequency-domain resources in some bands may be subdivided into bandwidth portions (BWPs). A BWP may be a contiguous block of frequency-domain resources allocated to one or more UEs 120 (e.g., a contiguous block of resource blocks). A UE 120 may be configured with both an uplink BWP and a downlink BWP (where the uplink BWP and downlink BWP may be the same BWP or different BWPs). BWPs may be dynamically configured and / or reconfigured (e.g., by sending DCI configuration to one or more UEs 120 via network node 110), meaning that BWPs may be adjusted in real-time (or near real-time) based on changing network conditions in the wireless communication network 100 and / or based on the specific requirements of one or more UEs 120. This allows for more efficient use of available frequency domain resources in the wireless communication network 100, as fewer frequency domain resources can be allocated to the BWP for UE 120 (which reduces the number of frequency domain resources that UE 120 needs to monitor), thus allowing more frequency domain resources to be distributed across multiple UE 120s. Therefore, the BWP can also assist in the implementation of such UE 120s by facilitating the configuration of smaller bandwidths for communications performed by lower-capacity UE 120s.

[0045] As described above, in some aspects, the wireless communication network 100 may be an IAB network, may include an IAB network, or may be included in an IAB network. In an IAB network, at least one network node 110 is an anchor network node communicating with a core network. The anchor network node 110 may also be referred to as an IAB donor (or "IAB donor"). The anchor network node 110 may be connected to the core network via a wired backhaul link. For example, the Ng interface of the anchor network node 110 may terminate at the core network. Additionally or alternatively, the anchor network node 110 may be connected to one or more devices in the core network that provide core access and mobility management functions (AMF). An IAB network typically also includes multiple non-anchor network nodes 110, which may also be referred to as relay network nodes or simply IAB nodes (or "IAB-nodes"). Each non-anchor network node 110 can directly communicate with the anchor network node 110 via a wireless backhaul link to access the core network, or can indirectly communicate with the anchor network node 110 via one or more other non-anchor network nodes 110 and an associated wireless backhaul link forming a backhaul path to the core network. Some anchor network nodes 110 or other non-anchor network nodes 110 can also directly communicate with one or more UEs 120 via a wireless access link carrying access services. In some examples, network resources used for wireless communication (such as time resources, frequency resources, and / or spatial resources) can be shared between the access link and the backhaul link.

[0046] In some examples, any network node 110 relaying communication may be referred to as a relay network node, a relay station, or simply a repeater. A repeater may receive communications from an upstream station (e.g., another network node 110 or UE 120) and transmit communications to a downstream station (e.g., UE 120 or another network node 110). In this case, the wireless communication network 100 may include or be referred to as a "multi-hop network." Figure 1 In the example shown, network node 110d (e.g., a relay network node) can communicate with network node 110a (e.g., a macro network node) and UE 120d to facilitate communication between network node 110a and UE 120d. Additionally or alternatively, UE 120 can be a relay station capable of relaying transmissions to or from other UE 120s, or can operate as such a relay station. UE 120 relaying communication can be referred to as a UE repeater or relay UE, etc.

[0047] UE 120 may be physically distributed throughout the wireless communication network 100, and each UE 120 may be stationary or mobile. UE 120 may be, may include, an access terminal, another terminal, a mobile station, or a subscriber unit, or may be included in an access terminal, another terminal, a mobile station, or a subscriber unit. UE 120 may be, or may include, a cellular phone (e.g., a smartphone), a personal digital assistant (PDA), a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet device, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device, a biometric device, a wearable device (e.g., a smartwatch, smart clothing, smart glasses, a smart wristband and / or smart jewelry (such as a smart ring or smart bracelet)), an entertainment device (e.g., a music device, a video device and / or a satellite radio), an extended reality (XR) device, a vehicle component or sensor, a smart meter or sensor, industrial manufacturing equipment, a Global Navigation Satellite System (GNSS) device (such as a Global Positioning System device or another type of positioning device), a UE function of a network node, and / or any other suitable device or function that can communicate via a wireless medium, or may be coupled to them.

[0048] UE 120 and / or network node 110 may include one or more chips, system-on-a-chip (SoC), chipsets, packages, or devices that individually or collectively constitute or include a processing system. The processing system includes processor (or “processing”) circuitry in the form of one or more processors, microprocessors, processing units (such as central processing units (CPUs), graphics processing units (GPUs), neural processing units (NPUs), and / or digital signal processors (DSPs)), processing blocks, application-specific integrated circuits (ASICs), programmable logic devices (PLDs) (such as field-programmable gate arrays (FPGAs)), or other discrete gate or transistor logic components or circuits (all of which are generally referred to herein individually as “processors” or collectively as “processors” or “processor circuitry”). One or more of these processors may be individually or collectively configured to perform the various functions or operations described herein. A processor group that can be configured or configured to perform a set of functions may include a first processor that can be configured or configured to perform a first function in the set, and a second processor that can be configured or configured to perform a second function in the set, or may include the entire processor group that is configured or configured to perform the set of functions.

[0049] The processing system may also include memory circuitry in the form of one or more memory devices, memory blocks, memory elements, or other discrete gate or transistor logic components or circuits, each of which may include tangible storage media such as random access memory (RAM) or read-only memory (ROM) or combinations thereof (all of which are generally referred to herein individually as "memory" or collectively as "memory" or "memory circuitry"). One or more of these memories may be coupled to one or more processors in the processor (e.g., operatively coupled, communicatively coupled, electronically coupled, or electrically coupled) and may store processor-executable code (such as software) individually or collectively, which, when executed by one or more processors in the processor, may configure one or more processors in the processor to perform the various functions or operations described herein. Additionally or alternatively, in some examples, one or more processors in the processor may be pre-configured to perform the various functions or operations described herein without being configured by software. The processing system may also include or be coupled to one or more modems (such as Wi-Fi (e.g., IEEE compliant) modems or cellular (e.g., 3GPP 4G LTE, 5G, or 6G compliant) modems). In some embodiments, one or more processors of the processing system include or implement one or more modems among the modems. The processing system may also include, or be coupled to, multiple radio components (collectively, “radio components”), multiple RF chains, or multiple transceivers, each of which may in turn be coupled to one or more antennas among a plurality of antennas. In some embodiments, one or more processors of the processing system include or implement one or more of the radio components, RF chains, or transceivers. UE 120 may be included or may be contained in a housing that houses components associated with UE 120, including the processing system.

[0050] Some UEs 120 may be considered Machine Type Communication (MTC) UEs, Evolved or Enhanced Machine Type Communication (eMTC) UEs, Further Enhanced eMTC (feMTC) UEs or Enhanced feMTC (efeMTC) UEs, or further evolutions thereof, all of which may be collectively referred to as "MTC UEs". MTC UEs may be, may include, or may be included in or coupled with the following: robots, unmanned aerial vehicles, remote devices, sensors, instruments, monitors, and / or location tags. Some UEs 120 may be considered IoT devices and / or may be implemented as NB-IoT (Narrowband IoT) devices. IoT UEs or NB-IoT devices may be, may include, or may be included in or coupled with the following: industrial machines, appliances, refrigerators, doorbell camera devices, home automation devices, and / or lighting fixtures, etc. Some UEs 120 may be considered customer premises equipment, which may include telecommunications equipment installed at a customer location (such as a home or office) to enable access to a service provider’s network (such as being included in or communicating with the wireless communication network 100).

[0051] Some UEs 120 can be categorized according to different categories associated with varying levels of complexity and / or capabilities. UEs 120 in the first category facilitate large-scale IoT within the wireless communication network 100 and offer lower complexity and / or lower cost compared to UEs 120 in the second category. UEs 120 in the second category may include mission-critical IoT devices, legacy UEs, baseline UEs, high-level UEs, advanced UEs, full-capability UEs, and / or premium UEs capable of ultra-reliable low-latency communication (URLLC), enhanced mobile broadband (eMBB), and / or precise positioning within the wireless communication network 100. UEs 120 in the third category may possess intermediate-level complexity and / or capabilities (e.g., capabilities between UEs 120 in the first category and UEs 120 in the second category). UEs 120 in the third category may be referred to as reduced-capacity UEs (“RedCap UEs”), intermediate-level UEs, NR lightweight UEs, and / or NR simplified UEs, etc. RedCap UEs bridge the gap in capabilities and complexity between NB-IoT devices and / or eMTC UEs and mission-critical IoT devices and / or premium UEs. RedCap UEs can include, for example, wearable devices, IoT devices, industrial sensors, and / or cameras associated with limited bandwidth, power capacity, and / or transmission range. RedCap UEs can support healthcare environments, building automation, power distribution, process automation, transportation and logistics, and / or smart city deployments, among others.

[0052] In some examples, two or more UEs 120 (e.g., shown as UE 120a and UE 120e) can communicate directly with each other using sidelink communication (e.g., without communicating through a network node 110 acting as an intermediary). As an example, UE 120a can send data, control information, or other signaling directly to UE 120e as sidelink communication. This contrasts with, for example, UE 120a first sending data to network node 110 in UL communication, and then that network node sending data to UE 120e in DL communication. In various examples, UE 120 can use peer-to-peer (P2P) communication protocols, device-to-device (D2D) communication protocols, vehicle-to-everything (V2X) communication protocols (which may include vehicle-to-vehicle (V2V) protocols, vehicle-to-infrastructure (V2I) protocols, and / or vehicle-to-pedestrian (V2P) protocols), and / or mesh network communication protocols to send and receive sidelink communication. In some deployments and configurations, network node 110 may schedule and / or allocate resources for sidelink communication between UEs 120 in the wireless communication network 100. In some other deployments and configurations, UE 120 (instead of network node 110) may perform or cooperate with or negotiate with one or more other UEs to perform scheduling operations, resource selection operations, and / or other operations for sidelink communication.

[0053] In various examples, in addition to half-duplex operation, some network nodes and UEs in the wireless communication network 100, including network node 110 and UE 120, can also be configured for full-duplex operation. Network node 110 or UE 120 operating in half-duplex mode can perform only one of transmission or reception during a specific time resource period (such as a specific time slot, symbol, or other time period). Half-duplex operation may involve time division duplex (TDD), where the DL transmission of network node 110 and the UL transmission of UE 120 do not occur in the same time resource (i.e., the transmissions do not overlap in time). In contrast, network node 110 or UE 120 operating in full-duplex mode can transmit and receive communications concurrently (e.g., within the same time resource). By operating in full-duplex mode, network node 110 and / or UE 120 can generally increase the capacity of the network and radio access links. In some examples, full-duplex operation may involve frequency division duplex (FDD), in which network node 110 performs DL transmission in a first frequency band or on a first component carrier, and UE 120 performs transmission in a second frequency band or on a second component carrier, the second frequency band or the second component carrier being different from the first frequency band or the first component carrier, respectively. In some examples, full-duplex operation may be enabled for UE 120 but not for network node 110. For example, UE 120 may simultaneously transmit UL to the first network node 110 and receive DL transmissions from the second network node 110 in the same time resources. In some other examples, full-duplex operation may be enabled for network node 110 but not for UE 120. For example, network node 110 may simultaneously transmit DL to the first UE 120 and receive UL transmissions from the second UE 120 in the same time resources. In some other examples, full-duplex operation may be enabled for both network node 110 and UE 120.

[0054] In some examples, UE 120 and network node 110 can perform MIMO communication. "MIMO" generally refers to the simultaneous transmission or reception of multiple signals (such as multiple layers or multiple data streams) using the same time and frequency resources. MIMO technology typically utilizes multipath propagation. MIMO can be implemented using various spatial processing or spatial multiplexing operations. In some examples, MIMO can support simultaneous transmission to multiple receivers, which is called multi-user MIMO (MU-MIMO). Some radio access technologies (RATs) can employ advanced MIMO techniques such as mTRP operation (including redundant transmission or reception on multiple TRPs), reciprocity in the time or frequency domain, single-frequency network (SFN) transmission, or noncoherent joint transmission (NC-JT).

[0055] In some aspects, the wireless communication device may include a communication manager 140 or a communication manager 150. As described in more detail elsewhere herein, the communication manager 140 or the communication manager 150 may: receive a transmission associated with one or more bits; and decode the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of one or more confidence level values ​​and an offset at least in part based on the number of one or more confidence level values. Additionally or alternatively, the communication manager 140 or the communication manager 150 may perform one or more other operations described herein.

[0056] As indicated above, Figure 1 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 1 The examples described are different.

[0057] Figure 2 This is a diagram illustrating an example network node 110 communicating with an example UE 120 in a wireless network according to the present disclosure.

[0058] like Figure 2 As shown, network node 110 may include a data source 212, a transmit processor 214, a transmit (TX) MIMO processor 216, a set of modems 232 (shown as 232a to 232t, where t≥1), a set of antennas 234 (shown as 234a to 234v, where v≥1), a MIMO detector 236, a receive processor 238, a data sink 239, a controller / processor 240, a memory 242, a communication unit 244, a scheduler 246, and / or a communication manager 150, etc. In some configurations, one or a combination of antennas 234, modems 232, MIMO detectors 236, receive processors 238, transmit processors 214, and / or TX MIMO processors 216 may be included in the transceiver of network node 110. The transceiver may be under the control of and used by one or more processors (such as controller / processor 240), and in some respects, may perform aspects of the methods, procedures and / or operations described herein in conjunction with processor-readable code stored in memory 242. In some respects, network node 110 may include one or more interfaces, communication components and / or other components that facilitate communication with UE 120 or another network node.

[0059] The terms “processor,” “controller,” or “controller / processor” can refer to one or more controllers and / or one or more processors. For example, references to “a / the processor,” “a / the controller / processor,” etc. (in the singular) should be understood as referring to a combination of… Figure 2The processor described refers to any one or more processors, such as a single processor or a combination of multiple different processors. The reference to "one or more processors" should be understood as a combination of references. Figure 2 Any one or more processors described herein. For example, one or more processors of network node 110 may include transmit processor 214, TX MIMO processor 216, MIMO detector 236, receive processor 238, and / or controller / processor 240. Similarly, one or more processors of UE 120 may include MIMO detector 256, receive processor 258, transmit processor 264, TX MIMO processor 266, and / or controller / processor 280.

[0060] In some aspects, a single processor can perform all operations described as being performed by one or more processors. In some aspects, a first set of one or more processors can perform a first operation described as being performed by that one or more processors, and a second set of one or more processors can perform a second operation described as being performed by that one or more processors. The processors in the first set and the processors in the second set can be the same set of processors or can be different sets of processors. The reference to "one or more memories" should be understood to refer to any one or more memories of the corresponding device, such as combined... Figure 2 The memory described. For example, an operation described as being performed by one or more memories can be performed by the same subset of the one or more memories or by different subsets of the one or more memories.

[0061] For downlink communication from network node 110 to UE 120, transmit processor 214 may receive data (“downlink data”) intended for use by UE 120 (or a set of UEs including UE 120) from data source 212 (such as a data pipeline or data queue). In some examples, transmit processor 214 may select one or more MCSs for UE 120 based on one or more Channel Quality Indicators (CQIs) received from UE 120. Network node 110 may process the data (e.g., including encoding the data) according to the MCS selected for UE 120 for transmission to UE 120 on the downlink, thereby generating data symbols. Transmit processor 214 may process system information (e.g., semi-static resource partitioning information (SRPI)) and / or control information (e.g., CQI requests, grants, and / or upper-layer signaling) and provide overhead symbols and / or control symbols. The transmitting processor 214 can generate reference symbols for reference signals (e.g., cell-specific reference signals (CRS), demodulation reference signals (DMRS), or channel state information (CSI) reference signals (CSI-RS)) and / or synchronization signals (e.g., primary synchronization signal (PSS) or secondary synchronization signal (SSS)).

[0062] The TX MIMO processor 216 can perform spatial processing (e.g., pre-decoding) on ​​data symbols, control symbols, overhead symbols, and / or reference symbols, where applicable, and can provide a set of output symbol streams (e.g., T output symbol streams) to a set of modems 232. For example, each output symbol stream can be provided to a corresponding modulator component (shown as MOD) of modem 232. Each modem 232 can use the corresponding modulator component to process (e.g., modulate) the corresponding output symbol stream (e.g., for Orthogonal Frequency Division Multiplexing (OFDM)) to obtain an output sample stream. Each modem 232 can further use the corresponding modulator component to process (e.g., convert to analog, amplify, filter, and / or up-convert) the output sample stream to obtain a time-domain downlink signal. Modems 232a to 232t can transmit a set of downlink signals (e.g., T downlink signals) together via a set of corresponding antennas 234.

[0063] Downlink signals may include DCI communication, MAC control element (MAC-CE) communication, RRC communication, downlink reference signals, or another type of downlink communication. Downlink signals may be transmitted on the PDCCH, PDSCH, and / or on another downlink channel. Downlink signals may carry one or more transport blocks (TBs) of data. A TB may be a data unit transmitted via the air interface in the wireless communication network 100. A data stream (e.g., from data source 212) may be encoded into multiple TBs for transmission via the air interface. The number of TBs used to carry data associated with a particular data stream may be associated with a TB size shared by multiple TBs. The TB size may be based on the radio channel conditions of the air interface, the MCS used to encode the data, downlink resources allocated for transmitting data, and / or other parameters, or otherwise associated with them. Generally, a larger TB size allows for a larger amount of data to be transmitted in a single transmission, reducing signaling overhead. However, a larger TB size may be more prone to transmission and / or reception errors than a smaller TB size, but such errors can be mitigated through more robust error correction techniques.

[0064] For uplink communication from UE 120 to network node 110, the uplink signal from UE 120 may be received by antenna 234, processed by modem 232 (e.g., demodulator component of modem 232, shown as DEMOD), detected where applicable by MIMO detector 236 (e.g., receive (Rx) MIMO processor), and / or further processed by receive processor 238 to obtain decoded data and / or control information. Receive processor 238 may provide the decoded data to data sink 239 (which may be a data pipeline, data queue, and / or another type of data sink) and provide the decoded control information to processors such as controller / processor 240.

[0065] Network node 110 may use scheduler 246 to schedule one or more UEs 120 for downlink or uplink communication. In some aspects, scheduler 246 may use DCI to dynamically schedule DL transmissions to and / or UL transmissions from UE 120. In some examples, scheduler 246 may allocate repetitive time-domain and / or frequency-domain resources that UE 120 may use for transmitting and / or receiving communication with RRC configuration (e.g., semi-static configuration), for example, to perform semi-persistent scheduling (SPS) or to configure configuration grant (CG) for UE 120.

[0066] One or more of the following may be included in the RF chain of network node 110: transmit processor 214, TX MIMO processor 216, modem 232, antenna 234, MIMO detector 236, receive processor 238, and / or controller / processor 240. The RF chain may include one or more filters, mixers, oscillators, amplifiers, analog-to-digital converters (ADCs), and / or other devices for converting analog signals (such as those used for transmission or reception via an air interface) to digital signals (such as those used for processing by one or more processors of network node 110). In some aspects, the RF chain may be a transceiver of network node 110, or may be included in such a transceiver.

[0067] In some examples, network node 110 may use communication unit 244 to communicate with the core network and / or other network nodes. Communication unit 244 may support wired and / or wireless communication protocols and / or connections, such as Ethernet, fiber optic, Common Public Radio Interface (CPRI), and / or wired or wireless backhaul, etc. Network node 110 may use communication unit 244 to send and / or receive data associated with UE 120, or to execute network control signaling, etc. Communication unit 244 may include transceivers and / or interfaces, such as network interfaces.

[0068] UE 120 may include a collection of antennas 252 (shown as antennas 252a to 252r, where r ≥ 1), a collection of modems 254 (shown as modems 254a to 254u, where u ≥ 1), a MIMO detector 256, a receive processor 258, a data sink 260, a data source 262, a transmit processor 264, a TX MIMO processor 266, a controller / processor 280, a memory 282, and / or a communication manager 140, etc. One or more components of UE 120 may be included in housing 284. In some aspects, one or a combination of antenna 252, modem 254, MIMO detector 256, receive processor 258, transmit processor 264, or TX MIMO processor 266 may be included in a transceiver included in UE 120. The transceiver may be under the control of and used by one or more processors (such as controller / processor 280), and in some respects, may perform aspects of the methods, procedures, or operations described herein in conjunction with processor-readable code stored in memory 282. In some respects, UE 120 may include another interface, another communication component, and / or another component that facilitates communication with network node 110 and / or another UE 120.

[0069] For downlink communication from network node 110 to UE 120, the set of antennas 252 can receive downlink communication or signals from network node 110 and can provide a set of received downlink signals (e.g., R received signals) to a set of modems 254. For example, each received signal can be provided to a corresponding demodulator component (shown as DEMOD) of modem 254. Each modem 254 can use the corresponding demodulator component to condition (e.g., filter, amplify, downconvert, and / or digitize) the received signal to obtain an input sample. Each modem 254 can use the corresponding demodulator component to further demodulate or process the input sample (e.g., for OFDM) to obtain a received symbol. MIMO detector 256 can obtain the received symbols from the set of modems 254, can perform MIMO detection on the received symbols where applicable, and can provide the detected symbols. The receiver processor 258 can process (e.g., decode) the detected symbols, provide the decoded data for the UE 120 to the data sink 260 (which may include a data pipeline, a data queue, and / or an application running on the UE 120), and provide the decoded control information and system information to the controller / processor 280.

[0070] For uplink communication from UE 120 to network node 110, the transmitting processor 264 may receive and process data (“uplink data”) from data source 262 (such as data pipelines, data queues, and / or applications running on UE 120) and control information from controller / processor 280. The control information may include one or more parameters, feedback, one or more signal measurements, and / or other types of control information. In some aspects, the receiving processor 258 and / or controller / processor 280 may determine one or more parameters related to the transmission of uplink communication for received signals (such as those received from network node 110 or another UE). One or more parameters may include a Reference Signal Received Power (RSRP) parameter, a Received Signal Strength Indicator (RSSI) parameter, a Reference Signal Received Quality (RSRQ) parameter, a Channel Quality Indicator (CQI) parameter, or a Transmit Power Control (TPC) parameter, etc. The control information may include indications of RSRP, RSSI, RSRQ, CQI, TPC, and / or another parameter. Control information can facilitate parameter selection and / or scheduling for UE 120 by network node 110.

[0071] Transmit processor 264 can generate reference symbols for one or more reference signals, such as uplink DMRS, uplink sounding reference signal (SRS), and / or another type of reference signal. Symbols from transmit processor 264 can be pre-decoded by TX MIMO processor 266 where applicable, and further processed by an assembly of modems 254 (e.g., for DFT-s-OFDM or CP-OFDM). TX MIMO processor 266 can perform spatial processing (e.g., pre-decoding) on ​​data symbols, control symbols, overhead symbols, and / or reference symbols where applicable, and can provide an assembly of output symbol streams (e.g., U output symbol streams) to the assembly of modems 254. For example, each output symbol stream can be provided to a corresponding modulator component (shown as MOD) of modem 254. Each modem 254 can use the corresponding modulator component to process (e.g., modulate) the corresponding output symbol stream (e.g., for OFDM) to obtain an output sample stream. Each modem 254 may further use a corresponding modulator component to process (e.g., convert to analog, amplify, filter, and / or upconvert) the output sample stream to obtain an uplink signal.

[0072] Modems 254a to 254u can transmit a set of uplink signals (e.g., R uplink signals or U uplink symbols) via a set of corresponding antennas 252. Uplink signals may include UCI communication, MAC-CE communication, RRC communication, or another type of uplink communication. Uplink signals can be transmitted on PUSCH, PUCCH, and / or another type of uplink channel. Uplink signals can carry one or more TBs of data. Sidelink data and control transmission (i.e., transmission directly between two or more UEs 120) typically uses techniques similar to those described for uplink data and control transmission and may use sidelink-specific channels such as the Physical Sidelink Shared Channel (PSSCH), Physical Sidelink Control Channel (PSCCH), and / or Physical Sidelink Feedback Channel (PSFCH).

[0073] One or more antennas in the set of antennas 252 or the set of antennas 234 may include one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays, etc., or may be included in one or more antenna panels, one or more antenna groups, one or more sets of antenna elements, or one or more antenna arrays, etc. Antenna panels, antenna groups, sets of antenna elements, or antenna arrays may include one or more antenna elements (within a single housing or multiple housings), a set of coplanar antenna elements, a set of non-coplanar antenna elements, or with one or more transmitting or receiving components (such as...) Figure 2An antenna module is a combination of one or more antenna elements coupled to one or more components. As used herein, "antenna" can mean one or more antennas, one or more antenna panels, one or more antenna groups, one or more collections of antenna elements, or one or more antenna arrays. "Antenna panel" can mean a group of antennas (such as antenna elements) arranged in an array or panel that can facilitate beamforming by manipulating the parameters of that group of antennas. "Antenna module" can mean a circuit that includes one or more antennas, and may also include one or more other components (such as filters, amplifiers, or processors) associated with integrating the antenna module into a wireless communication device.

[0074] In some examples, each antenna element of antenna 234 or antenna 252 may include one or more sub-elements for radiating or receiving radio frequency signals. For example, a single antenna element may include a first sub-element cross-polarized with a second sub-element, which can be used to independently transmit cross-polarized signals. Antenna elements may include patch antennas, dipole antennas, and / or other types of antennas arranged in a linear pattern, a two-dimensional pattern, or another pattern. The spacing between antenna elements can allow signals with a desired wavelength transmitted individually by the antenna elements to interact or interfere (e.g., to form a desired beam) in various directions. For example, given a desired wavelength or frequency range, the spacing may provide a quarter wavelength, half a wavelength, or another fraction of the wavelength between adjacent antenna elements to allow desired constructive and destructive interference modes of signals transmitted by individual antenna elements within that desired range.

[0075] The amplitude and / or phase of signals transmitted via antenna elements and / or sub-elements can be modulated and (e.g., by manipulating phase shifts, phase offsets, and / or amplitudes) shifted relative to each other to generate one or more beams; this is known as beamforming. The term "beam" can refer to the directional transmission of a wireless signal toward a receiving device or otherwise in a desired direction. "Beam" can also generally refer to the direction associated with such directional signal transmission, the set of directional resources associated with the signal transmission (e.g., angle of arrival, horizontal direction, and / or vertical direction), and / or a set of parameters indicating one or more aspects of the directional signal, the direction associated with the signal, and / or the set of directional resources associated with the signal. In some implementations, antenna elements can be individually selected or deselected for the directional transmission of a signal (or multiple signals) by controlling the amplitude of one or more corresponding amplifiers and / or the phase of the signal to form one or more beams. The shape of the beam (such as amplitude, width, and / or the presence of sidelobes) and / or the direction of the beam (such as the angle of the beam relative to the surface of the antenna array) can be dynamically controlled by modifying the phase shifts, phase offsets, and / or amplitudes of multiple signals relative to each other.

[0076] Different UEs 120 or network nodes 110 may include different numbers of antenna elements. For example, UE 120 may include a single antenna element, two antenna elements, four antenna elements, eight antenna elements, or different numbers of antenna elements. As another example, network node 110 may include eight antenna elements, 24 antenna elements, 64 antenna elements, 128 antenna elements, or different numbers of antenna elements. Generally speaking, a larger number of antenna elements provides increased control over the parameters used for beamforming compared to a smaller number of antenna elements, while a smaller number of antenna elements may be less complex to implement and can use less power. Multiple antenna elements can support multi-layer transmission, in which the same time and frequency resources are used to utilize spatial multiplexing to transmit a first layer of communication (which may include a first data stream) and a second layer of communication (which may include a second data stream).

[0077] Although Figure 2 The boxes in the diagram are illustrated as different components, but the functions described above with respect to these boxes may be implemented in a single hardware, software, or combined component, or in various combinations of components. For example, the functions described with respect to transmit processor 264, receive processor 258, and / or TX MIMO processor 266 may be performed by or under the control of controller / processor 280.

[0078] Figure 3 This is an illustration of an example decomposed base station architecture 300 according to the present disclosure. One or more components of the example decomposed base station architecture 300 may be, may include, or may be included in one or more network nodes (such as one or more network nodes 110). The decomposed base station architecture 300 may include a CU 310, which may communicate directly with the core network 320 via a backhaul link, or may communicate indirectly with the core network 320 via one or more decomposed control units (such as non-RT RIC 350 and / or near-RT RIC 370 associated with a Service Management and Orchestration (SMO) framework 360 (e.g., via an E2 link)). The CU 310 may communicate with one or more DU 330s via a corresponding midhaul link (such as via an F1 interface). Each DU 330 may communicate with one or more RU 340s via a corresponding fronthaul link. Each RU 340 may communicate with one or more UE 120s via a corresponding RF access link. In some deployments, a UE 120 may be served simultaneously by multiple RU 340s.

[0079] Each component in the decomposed base station architecture 300 (including CU 310, DU 330, RU 340, near-RT RIC 370, non-RT RIC 350, and SMO frame 360) may include one or more interfaces or be coupled to one or more interfaces for receiving or transmitting signals, such as data or information, via wired or wireless transmission media.

[0080] In some respects, the CU 310 can be logically divided into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP units can communicate bidirectionally with the CU-CP units via an interface such as an E1 interface. The CU 310 can be deployed to communicate with one or more DU 330s for network control and signaling, as needed. Each DU 330 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RU 340s. For example, the DU 330 may host various layers, such as the RLC layer, MAC layer, or one or more PHY layers (such as one or more high PHY layers or one or more low PHY layers). Each layer (which may also be referred to as a module) can be implemented using an interface for signaling to other layers (and modules) hosted by the DU 330, or for signaling to control functions hosted by the CU 310. Each RU 340 may implement lower-layer functionality. In some respects, the real-time and non-real-time aspects of communication with the control plane and user plane of the RU 340 can be controlled by the corresponding DU 330.

[0081] The SMO framework 360 supports RAN deployment and provisioning for both non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO framework 360 supports the deployment of dedicated physical resources for RAN coverage requirements, which can be managed via operation and maintenance interfaces such as the O1 interface. For virtualized network elements, the SMO framework 360 can interact with cloud computing platforms such as the Open Cloud (O-Cloud) platform 390 to perform network element lifecycle management (such as instantiating virtualized network elements) via cloud computing platform interfaces such as the O2 interface. Virtualized network elements may include, but are not limited to, CU 310, DU 330, RU 340, non-RT RIC 350, and / or near-RT RIC 370. In some aspects, the SMO framework 360 can communicate with hardware aspects of the 4G RAN, 5G NR RAN, and / or 6G RAN (such as the Open eNB (O-eNB) 380) via the O1 interface. Additionally or alternatively, the SMO framework 360 can communicate directly with each of one or more RUs 340 via the corresponding O1 interface. In some deployments, this configuration enables each DU 330 and CU 310 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

[0082] The non-RT RIC 350 may include or implement logical functions that enable non-real-time control and optimization of RAN elements and resources, including artificial intelligence / machine learning (AI / ML) workflows for model training and updates, and / or policy-based guidance of applications and / or features in the near-RT RIC 370. The non-RT RIC 350 may be coupled to or communicate with the near-RT RIC 370, such as via an A1 interface. The near-RT RIC 370 may include or implement logical functions that enable near real-time control and optimization of RAN elements and resources via an interface, such as an E2 interface, through data collection and actions, connecting one or more CU 310s, one or more DU 330s, and / or O-eNBs to the near-RT RIC 370.

[0083] In some aspects, to generate AI / ML models to be deployed in the near-RT RIC 370, the non-RT RIC 350 may receive parameters or external enrichment information from an external server. This information can be utilized by the near-RT RIC 370 and can be received from non-network data sources or network functions at the SMO framework 360 or the non-RT RIC 350. In some examples, the non-RT RIC 350 or near-RT RIC 370 may modulate RAN behavior or performance. For example, the non-RT RIC 350 may monitor long-term trends and patterns in performance and may employ AI / ML models to perform corrective actions via the SMO framework 360 (such as reconfiguration via the O1 interface) or via the creation of RAN management policies (such as A1 interface policies).

[0084] As indicated above, Figure 3 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 3 The examples described are different.

[0085] Figure 1 , Figure 2 or Figure 3 Network node 110, its controller / processor 240, UE 120, UE 120's controller / processor 280, CU 310, DU 330, RU 340, or any other component may implement or perform one or more techniques associated with decoding using the average and offset associated with the confidence level value, as described in more detail elsewhere herein. For example, network node 110's controller / processor 240, UE 120's controller / processor 280, CU 310, DU 330, RU 340, or any other component may implement or perform one or more operations associated with decoding using the average and offset associated with the confidence level value, as described in more detail elsewhere herein. Figure 2 Any other component, CU 310, DU 330, or RU 340 may (alone or in combination with one or more other processors) perform or direct, for example... Figure 12The operation of process 1200 or other processes as described herein. Memory 242 may store data and program code for network node 110, CU 310, DU 330, or RU 340. Memory 282 may store data and program code for UE 120. In some examples, memory 242 or memory 282 may include a non-transitory computer-readable medium storing instruction sets (e.g., code or program code) for wireless communication. Memory 242 may include one or more memories, such as a single memory or multiple different memories (of the same or different types). Memory 282 may include one or more memories, such as a single memory or multiple different memories (of the same or different types). For example, the instruction set may be made to be executed by one or more processors of network node 110, UE 120, CU 310, DU 330, or RU 340 (e.g., directly, or after compilation, transformation, or interpretation). Figure 12 The process 1200 or other processes as described herein. In some examples, the execution instructions may include run instructions, conversion instructions, compilation instructions, and / or interpretation instructions, etc. In some aspects, the wireless communication device described herein is network node 110, is included in network node 110, or includes... Figure 2 One or more components of the network node 110 shown. In some aspects, the wireless communication device described herein is UE 120, is included in UE 120, or includes... Figure 2 One or more components of the UE 120 shown.

[0086] In some aspects, the wireless communication device includes: components for receiving transmissions associated with one or more bits; and / or components for decoding the transmissions using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and at least partially based on an offset from the number of one or more confidence level values. In some aspects, components for the wireless communication device to perform the operations described herein may include, for example, one or more of a communication manager 150, a transmit processor 220, a TX MIMO processor 230, a modem 232, an antenna 234, a MIMO detector 236, a receive processor 238, a controller / processor 240, a memory 242, or a scheduler 246. In some aspects, components for the wireless communication device to perform the operations described herein may include, for example, one or more of a communication manager 140, an antenna 252, a modem 254, a MIMO detector 256, a receive processor 258, a transmit processor 264, a TX MIMO processor 266, a controller / processor 280, or a memory 282.

[0087] Figure 4 This is an illustration of example 400 of the LDPC code according to this disclosure.

[0088] LDPC codes can be a class of linear error-correcting codes (e.g., graph-based codes) defined by a sparse parity check matrix 410. The sparse parity check matrix 410 can be characterized by low-density entries with values ​​of 1 (hence the name "low-density parity"). From the transmitter's perspective, LDPC encoding is relatively straightforward, where the transmitter (or LDPC encoder) multiplies one or more message bits with the parity check matrix to generate a code block (or codeword).

[0089] However, LDPC decoding is a more complex and iterative process designed to correct errors in the received data. For example, LDPC decoding techniques typically use a sparse parity check matrix 410 and the received data to improve the estimation of the original message bits. LDPC decoding typically uses a belief propagation algorithm, also known as a sum-product algorithm, which operates on a factor graph representation 420 (e.g., a graph) of the code block, where messages can be iteratively exchanged between variable nodes (representing bits) and check nodes (representing parity check equations). LDPC codes allow for low-complexity decoding and / or encoding using local message passing. LDPC codes are capable of achieving error correction performance at larger block lengths for a variety of channels.

[0090] As indicated above, Figure 4 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 4 The examples described are different.

[0091] Figure 5 This is a diagram illustrating example 500 of confidence propagation decoding according to this disclosure.

[0092] LDPC decoding can be performed over multiple iterations (e.g., decoding iterations). An iteration may involve the variable node updating the corresponding confidence about the bit value based on information received from the connected check node, or the check node updating the corresponding confidence based on information from the connected variable node.

[0093] For example, as shown by reference numeral 510 in the attached figure, a variable node (“VN”) can receive channel information. The variable node can use the following relationship to configure messages. Perform initialization: ,in This is the log-likelihood ratio (LLR) value. (Message) (For example, This can be an external message that the variable node wants to pass to the check node. The LLR value can indicate the confidence level at which a zero-bit or one-bit value is sent.

[0094] As shown by reference numeral 520 in the attached figure, the iteration may involve the verification node (“CN”) receiving messages from the corresponding variable node. , and The verification node can use the following verification node kernel to generate messages. : The verification node can output messages to the variable node. .

[0095] As shown by reference numeral 530 in the attached figure, iteration may involve variable nodes receiving messages from the corresponding verification nodes. , and Variable nodes can use the following variable node kernels to generate one or more messages. : The variable node can output messages to the verification node. .

[0096] The process can continue for several iterations until LDPC decoding succeeds or fails. For example, the process can continue until a predefined number of iterations has been reached or certain stopping criteria are met. Examples of stopping criteria may include satisfying all parity equations, the bit error rate reaching an acceptable level, etc.

[0097] The complexity of belief propagation decoding scales with graph density (which can be sparse) and approaches maximum likelihood decoding at larger code lengths. However, periodicity and other problematic objects in the graph can degrade the performance of belief propagation decoding. Furthermore, belief propagation decoding may involve the implementation of the check node kernel, which is at least in part due to the presence of a hyperbolic tangent function in the check node kernel. ) and inverse hyperbolic tangent function ( It is not simple, but complex.

[0098] Low-complexity variants of the parity node kernel can reduce parity node complexity. Examples of such low-complexity variants include Finite Letter Iteration Decoding (FAID), Bit Flip Decoding, min-sum approximation, etc. For example, min-sum approximation can be a hardware-friendly implementation.

[0099] As indicated above, Figure 5 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 5 The examples described are different.

[0100] Figure 6 This is a diagram illustrating example 600 of the min-sum approximation according to this disclosure.

[0101] As shown in the figure, the verification node 610 can process messages from variable nodes 620(1)-620(3) simultaneously. , and and send the message , and Output to variable nodes 620(4)-620(6), where one or more of variable nodes 620(4)-620(6) may be the same as or different from variable nodes 620(1)-620(3). In message processing... , and At that time, the verification node 610 can retain external message constraints, thereby transmitting back each message (e.g., message) to the variable node. , and It cannot contain information received from the variable node (e.g., messages). , and ).

[0102] Validation node 610 can be approximated using min-sum. To process messages , and For example, check node 610 can implement the min-sum approximation using the following pseudocode, where "magn" refers to the input array of magnitudes and "degc" refers to the degree of check node 610 (e.g., the number of input messages, such as messages). , and "Item" can refer to a confidence level value (e.g., ).

[0103] Calculate the minterm:

[0104]

[0105] Calculation output:

[0106]

[0107] The min-sum approximation can be the second approximation of the check node kernel. The first approximation of the check node kernel can be the exponential approximation: .For example,

[0108] The numerator and denominator are the sum of exponential terms. Because Since ≥0, the numerator and denominator can be approximated as exponential terms with the largest exponent (e.g., the largest degree) as follows: Because the check node kernel generates non-negative values, the result of the exponential approximation can be limited to non-negative values ​​as follows: The min-sum approximation allows for the analysis (or "traversal") of the input message set once. While less complex than the check node kernel, the exponential approximation may involve floating-point operations using the natural logarithm and exponential functions, which can be computationally intensive.

[0109] The second approximation of the check node kernel can be derived, at least in part, based on the fact that the dominant term in the sum of exponent terms is the exponent term with the largest exponent: In some examples, an approximation of the sum of exponential terms is used, and because... Since ≥0, the exponent can be simplified as follows: (It is a min-sum approximation).

[0110] In the min-sum approximation, the dominant term is the one with the smallest magnitude. The min-sum approximation works well if one exponent is significantly larger than the others (e.g., if one term is the dominant term). For example, if Individual Index , ... If the dominant (e.g., largest) factors are close to each other (otherwise, the number of dominant factors can be reduced), then the exponential approximation formula can be approximated as: Therefore, the sum of exponential terms with close exponents can be approximated as the sum of exponential terms whose exponents are replaced by the average of the exponents. For example, if and , If ) = (0.368, 0.018, 0.018), then In another example, if and , )=(0.368,3.443x 3.443x ),but For convenience, It is assumed to be non-negative.

[0111] However, the min-sum approximation is ineffective when one term is not dominant. For example, if and , If ) = (0.368, 0.368, 0.368), then Therefore, in many cases, the min-sum approximation may result in a significant loss of error correction capability.

[0112] As indicated above, Figure 6 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 6 The examples described are different.

[0113] Figure 7 These are illustrations of Examples 700 and 710, which illustrate mathematical functions according to this disclosure. Example 700 shows a monotonically decreasing function. Example 710 illustrates a nonnegative function. As indicated above, Figure 7 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 7 The examples described are different.

[0114] Figure 8 This is a diagram illustrating an example 800 associated with verification node operation according to this disclosure. Wireless communication device (“WCD”) 810 and wireless communication device 820 may communicate with each other. Wireless communication device 810 and / or wireless communication device 820 may be a network node (e.g., network node 110), a UE (e.g., UE 120), etc.

[0115] As shown by reference numeral 830 in the accompanying drawings, wireless communication device 810 can transmit a transmission associated with one or more bits, and wireless communication device 820 can receive the transmission. The transmission can be associated with one or more bits because the transmission can deliver one or more bits to wireless communication device 820. For example, the transmission can be as described above... Figure 1 or Figure 2 Any suitable sender as described.

[0116] As shown by reference numeral 840 in the accompanying drawings, the wireless communication device 820 can decode the transmission. The wireless communication device 820 can decode the transmission using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and an offset at least partially based on the number of one or more confidence level values. The confidence level can be associated with one or more bits because the confidence level can be the confidence level at which the wireless communication device 810 transmits one or more bits as corresponding values ​​(e.g., a zero-bit value or a one-bit value). For example, the confidence level could be... (For example, the LLR value). In some examples, the average of one or more confidence level values ​​can be... ,in Minimum An index of the magnitude. In some examples, the offset, at least in part, based on the number of one or more confidence level values, can be... .

[0117] In some examples, the verification node of the wireless communication device 820 can be achieved by using the verification node kernel. The verification node operation is performed to decode the transmission, whereby... yes The number (e.g., if the verification node operation is against) and To perform the operation, =3). The verification node kernel can be derived as follows. The min-sum approximation can be generalized by establishing an upper bound: Therefore, the following relationship produces a closer approximation than the min-sum approximation: In some examples, This is due to the convexity of the exponential function: The convexity of an exponential function may be due to the function's... Monotonically decreasing sum function Non-negative.

[0118] Therefore, the verification node kernel can be based at least in part on inequalities. The inequality can be further simplified to = .exist In this case, it can be obtained from Recovering the min-sum approximation (e.g., It can produce a min-sum approximation). The check node kernel can be called a "dominant decoder" or "dominant decoder kernel" because the wireless communication device 820 can dominate. Perform the operation on the item.

[0119] Wireless communication device 820 can decode the transmission by applying a check node operation to an amplitude value close to the minimum amplitude value. For example, wireless communication device 820 can determine... (where the difference threshold) It is a fixed parameter that is greater than or equal to zero, and It is the minimum amplitude), and for Apply validation node operations. In some examples, applying validation node operations may involve identifying the minimum item (e.g., In some examples, the verification node of the wireless communication device 820 can determine the output of the min-sum approximation (e.g., the min-sum kernel) and output the minimum upper limit. In some examples, The number of items in (e.g., The upper limit can be defined by the parameter M, which reduces complexity.

[0120] The dominant decoder kernel can be implemented in the hardware of the wireless communication device 820. In some examples, using the dominant decoder, the wireless communication device 820 can analyze (or "traverse") the input message set twice: the first traversal is used to identify minterms (e.g., ), and the second traversal is used to identify the minterms. Any item within (e.g., satisfying) (Any item). In some examples, the wireless communication device 820 may use a dominant decoder in early iterations and a min-sum approximation in later iterations, which improves convergence speed. The wireless communication device 820 may implement the dominant decoder kernel according to the following pseudocode.

[0121] Calculate the minterm:

[0122]

[0123] Calculate and sum:

[0124]

[0125] Output calculation:

[0126]

[0127] In some respects, each confidence level in one or more confidence levels can be equal to the minimum of a plurality of confidence levels that include one or more confidence levels. For example, D can be equal to zero. With D=0, the explicit decoder can be simplified to... ,in It can be a minterm (e.g., the term with the smallest magnitude across all confidence levels). And |S| can be the count of minterms. Unlike the offsets used in offset min-sum (OMS) decoders (which are optimized using density evolution simulations and fixed at runtime), the dominant decoder can be dynamically applied depending on the number of minimum quantity terms (e.g., The offset of the number of items Therefore, with D=0, the dominant decoder can be called the Dynamic Offset min-sum (DOMS) decoder.

[0128] The wireless communication device 820 can use the following pseudocode to implement the DOMS decoder.

[0129] Calculate the minterm:

[0130]

[0131] Calculation output:

[0132]

[0133] In some aspects, decoding the transmission may include using a counter to identify one or more confidence level values. For example, the wireless communication device 820 may analyze items in one pass of the DOMS decoder. For example, at the beginning of the pass, the first item analyzed by the wireless communication device 820 may be an initial candidate minterm, and the wireless communication device 820 may increment the counter by one for each additional item equal to the initial candidate minterm. When another candidate minterm less than the initial candidate minterm is detected in the pass, the wireless communication device 820 may reset the counter and increment the counter by one for each additional item equal to that other candidate minterm. Therefore, at the end of the pass, the wireless communication device 820 may have identified the minterms among the analyzed items and the number of occurrences of that minterm.

[0134] In some aspects, decoding the transmission involves discretizing one or more confidence level values. For example, wireless communication device 820 may round each confidence level value to the nearest integer. For example, wireless communication device 820 may discretize each confidence level value before performing a traversal of the DOMS decoder. Discretize it.

[0135] In some respects, one or more confidence level values ​​may be within a non-zero difference threshold from the minimum of a plurality of confidence level values ​​that include one or more confidence level values. For example, D may be greater than zero. In some examples, the wireless communication device 820 may use a dominant decoder for D>0 to perform two traversals.

[0136] For example, if = (0, 2, 31, 31, 31, 31, 31), then the dominant decoder average for D=2 can be (0, 2), and the dominant decoder output can be -log(2) + 1 = 0.30685 (compared to the min-sum approximation output of 0). In another example, if = (5,5,7,7,31,31,31,31), then the dominant decoder average for D=2 can be (5,5,7,7), and the dominant decoder output can be -log(4)+6.5=4.6137. In this example, the dominant decoder is better than the min-sum approximation output of 5.

[0137] In some aspects, decoding the transmission involves discretizing the average of one or more confidence level values. For example, wireless communication device 820 may discretize the average for D>0. Discretization is performed. In some examples, the wireless communication device 820 may use integer division and... Perform rounding down. In some examples, wireless communication device 820 can... Round to the nearest integer (e.g., wireless communication device 820 can round to the nearest integer). (Perform rounding up or down). For example, wireless communication device 820 can use modulo operations and remainders, as shown in the following pseudocode.

[0138]

[0139] In some aspects, decoding the transmission may include discretizing the offset. For example, the wireless communication device 820 may discretize the offset in any suitable case (e.g., for D≥0). For example, in the case of D=0, the wireless communication device 820 may discretize the DOMS decoder. For example, in a given kernel for the DOMS decoder... In this case, wireless communication device 820 can be evaluated It then rounds up to the maximum check node degree. When D > 0, the wireless communication device 820 can perform a check on the dominant decoder. Discretization, including... Discretize it.

[0140] In some respects, discretizing the offset may include at least partially based on a lookup table. For example, for D≥0, a lookup table can be used to discretize the offset. Discretization (e.g., quantization) is performed. The wireless communication device 820 may store a lookup table during compile time.

[0141] In some aspects, discretizing the average of one or more confidence levels may include rounding the average of one or more confidence levels in a certain direction, and decoding the transmission may also include discretizing the offset by rounding the offset in that direction. For example, when D>0, the wireless communication device 820 may round the average and the offset in the same direction. For example, in a given In some cases, the wireless communication device 820 can round A and B in the same direction. In some examples, the wireless communication device 820 can round both A and B up. In some examples, the wireless communication device 820 can round both A and B down.

[0142] As indicated above, Figure 8 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 8 The examples described are different.

[0143] Figure 9 This is a diagram illustrating Example 900 of the lookup table according to this disclosure.

[0144] The lookup table includes the corresponding Row 910 contains the values ​​and row 920 contains the corresponding discretized offset values, each discretized offset value and The values ​​correspond. As shown in the figure, the lookup table contains nineteen pairs. Values ​​and discretization offset values. For example, wireless communication device 820 can identify... The value can be identified using a lookup table instead of calculating the corresponding discretization offset value.

[0145] As indicated above, Figure 9 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 9 The examples described are different.

[0146] Using the average and offset of one or more confidence levels to decode the transmission improves error correction performance, making the decoding result closer to confidence propagation, while preserving the hardware-friendly implementation of the min-sum approximation. For example, the check node kernel described in this paper can bridge the gap between check node kernels. Approximate with min-sum The performance gap in error correction between the two approaches can be bridged. For example, the check node kernel presented in this paper can improve performance by incorporating additional terms into the approximation. By dynamically selecting which terms to average, the dominant decoder can significantly outperform kernels that use static averaging, such as kernels that average using a fixed number of elements (e.g., by averaging the smallest M terms). The check node kernel can also reduce the hardware complexity that is increased by sorting the input magnitudes. For example, the check node kernel can utilize a low-complexity heuristic to select S without sacrificing performance improvements. Thus, the check node kernel can be a low-complexity kernel (e.g., less than twice the complexity of the min-sum approximation), bridging the performance gap between the min-sum approximation and the product approximation. For example, the check node kernel can provide significant gains in error correction performance and convergence speed, resulting in fewer cycles, reduced power consumption, and faster results.

[0147] Using different numbers of layers, in a basic Figure 1 Simulations were performed on a 5G NR LDPC channel with additive white Gaussian noise (AWGN). A higher number of layers involving more parity equations can be used on channels with poorer conditions. Tables 1 and 2 below illustrate the simulation results. Tables 1 and 2 will define the target metrics. Associated with target layer numbers of 4, 8, and 12. In some examples, Where “BLER” refers to “block error rate” and “SNR” refers to “signal-to-noise ratio”. Tables 1 and 2 confirm that the check node kernel described in this paper is superior to the baseline method.

[0148]

[0149] Table 1

[0150]

[0151] Table 2

[0152] Figures 10A to 10D These are illustrations of example 1000A-1000D showing simulation results involving a dominant decoder according to this disclosure.

[0153] refer to Figure 10A Example 1000A shows a graph comparing the baseline method with the dominant decoder for D=0, D=1, and D=2 for a fading channel simulated using Tapped Delay Line (TDL) A (TDLA). Reference Figure 10B Example 1000B shows a graph comparing the baseline method with the dominant decoder for D=0, D=1, and D=2 for a fading channel simulated using TDL C (TDLC). Reference Figure 10C Example 1000C shows a graph comparing the baseline method with the dominant decoder for D=0, D=1, and D=2 for analog spurious channels. (Reference) Figure 10D Example 1000D shows a graph comparing the baseline method with the dominant decoder for an analog dynamic spectrum sharing (DSS) channel with D=0. Examples 1000A-1000D use a throughput metric 1010 on carrier-to-interference-plus-noise ratio (CINR) to perform the corresponding comparison. As shown, the dominant decoder is at least as robust as the min-sum approximation on a variety of channels, such as fading channels, spurious channels, and DSS channels.

[0154] As indicated above, Figures 10A to 10D This is provided as an example. Other examples are available with reference to [the relevant information]. Figures 10A to 10D The examples described are different.

[0155] Each confidence level value in one or more confidence levels is equal to the minimum of the multiple confidence levels, providing minimal increase in complexity without introducing problems involving finite precision. For example, from a performance perspective, the DOMS decoder can... Significant improvements are offered in terms of metrics.

[0156] Tables 3 and 4 below illustrate the simulation results involving the DOMS decoder. Tables 3 and 4 demonstrate that the DOMS decoder offers superior performance.

[0157]

[0158] Table 3

[0159]

[0160] Table 4

[0161] Figure 11A and Figure 11B These are illustrations of example 1100A and example 1100B illustrating simulation results involving a DOMS decoder according to this disclosure.

[0162] refer to Figure 11A Example 1100A shows the use of Metric 1110 is used to compare the graphs of the baseline method, the min-sum approximation, and the DOMS decoder. (Reference) Figure 11B Example 1100B shows a graph comparing the baseline method, the min-sum approximation, and the DOMS decoder using the improved percentage metric 1120. As shown, the DOMS decoder can be compared relative to... Metric 1110 and the improved percentage metric 1120 outperform the baseline method and the min-sum approximation.

[0163] As indicated above, Figure 11A and Figure 11B This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 11A and Figure 11B The examples described are different.

[0164] Using counters to identify one or more confidence level values ​​allows the DOMS kernel to be implemented in a single pass, which is approximately equivalent to min-sum. For example, the DOMS kernel can avoid performing multiple passes for 5G NR LDPC, which can have up to nineteen check nodes. Therefore, the DOMS kernel reduces the complexity associated with performing multiple passes.

[0165] For one or more confidence levels Discretization enables the DOMS decoder to identify multiple [items / entities]. Item. For example, in the absence of... When discretization is performed, The terms can be floating-point, and therefore can not be equal to any other. Item. Therefore, for Discretization can make The items can be equal to each other, thereby improving the performance of the DOMS decoder.

[0166] Discretizing the average of one or more confidence levels can make the dominant decoder more hardware-friendly relative to the average. For example, the entire Operations can be quantized, rather than being calculated using floating-point arithmetic. And then quantize the back-check node precision (e.g., round) Therefore, finite precision can be used instead of floating-point precision to avoid performing check node operations using floating-point arithmetic.

[0167] Rounding the average and offset in the same direction can reduce errors. For example, because Including the difference between A and B, rounding A and B in the same direction (e.g., rounding A and B up or rounding A and B down) produces a lower error than rounding A and B in opposite directions (e.g., rounding A up and B down, or rounding A down and B up). Furthermore, for... Rounding may be more efficient than using a lookup table.

[0168] Discretizing the offset makes the dominant decoder more hardware-friendly relative to the offset. For example, the entire Operations can be quantized, rather than being calculated using floating-point arithmetic. And then quantize the back-check node precision (e.g., round) Therefore, finite precision can be used instead of floating-point precision to avoid performing check node operations using floating-point arithmetic.

[0169] Table 5 below shows the simulation results, which demonstrate that the discretized DOMS decoder can achieve no loss compared to the non-discrete DOMS decoder.

[0170]

[0171] Table 5

[0172] Figure 12 This is a diagram illustrating an example process 1200 performed, for example, at a wireless communication device or apparatus of a wireless communication device according to this disclosure. Example process 1200 is an example in which an apparatus or wireless communication device (e.g., network node 110 or UE 120) performs operations associated with decoding using an average value and an offset associated with a confidence level value.

[0173] like Figure 12 As shown, in some aspects, process 1200 may include receiving a transmission associated with one or more bits (block 1210). For example, a wireless communication device (e.g., using...) Figure 13 The depicted receiving component 1302 and / or communication manager 1306, or using Figure 14The depicted receiving component 1402 and / or communication manager 1406 can receive transmissions associated with one or more bits, as described above.

[0174] like Figure 12 Further shown, in some aspects, process 1200 may include decoding the transmission using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and at least in part based on an offset from the number of one or more confidence level values ​​(box 1220). For example, a wireless communication device (e.g., using...) Figure 13 The described communication manager 1306, or using Figure 14 The communication manager 1406 described above can decode the transmission using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and an offset based at least in part on the number of one or more confidence level values.

[0175] Process 1200 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere in this document.

[0176] In the first aspect, each of the one or more confidence level values ​​is equal to the minimum of the multiple confidence level values ​​that include the one or more confidence level values.

[0177] In the second aspect, decoding the transmission, either alone or in combination with the first aspect, includes using a counter to identify one or more confidence level values.

[0178] In the third aspect, decoding the transmission, either alone or in combination with one or more of the first and second aspects, includes discretizing one or more confidence level values.

[0179] In the fourth aspect, either alone or in combination with one or more of the first to third aspects, one or more confidence level values ​​are within a non-zero difference threshold from the minimum of a plurality of confidence level values ​​including one or more confidence level values.

[0180] In the fifth aspect, decoding the transmission, either alone or in combination with one or more of the first to fourth aspects, includes discretizing the average of one or more confidence level values.

[0181] In the sixth aspect, discretizing the average of one or more confidence level values, either alone or in combination with one or more of the first to fifth aspects, includes rounding the average of one or more confidence level values ​​in a certain direction, and decoding the transmission also includes discretizing the offset by rounding the offset in that direction.

[0182] In the seventh aspect, decoding the transmission, either alone or in combination with one or more of the first to sixth aspects, includes discretizing the offset.

[0183] In the eighth aspect, discretizing the offset, either alone or in combination with one or more of the first to seventh aspects, includes discretizing the offset at least in part based on a lookup table.

[0184] In the ninth aspect, alone or in combination with one or more of the first to eighth aspects, the wireless communication device is a UE.

[0185] In the tenth aspect, alone or in combination with one or more of the first to ninth aspects, the wireless communication device is a network node.

[0186] although Figure 12 An example box of process 1200 is shown, but in some respects, process 1200 may include... Figure 12 The boxes depicted may be fewer, different, or arranged differently compared to additional boxes. Alternatively, two or more boxes in process 1200 may be executed in parallel.

[0187] Figure 13 This is a diagram of an example device 1300 for wireless communication according to the present disclosure. Device 1300 may be a UE, or a UE may include device 1300. In some aspects, device 1300 includes a receiving component 1302, a transmitting component 1304, and / or a communication manager 1306 that can communicate with each other (e.g., via one or more buses and / or one or more other components). In some aspects, communication manager 1306 is combined with... Figure 1 The described communication manager 140. As shown, device 1300 can communicate with another device 1308 (such as a UE or a network node (such as a CU, DU, RU or base station)) using receiving component 1302 and transmitting component 1304.

[0188] In some respects, device 1300 can be configured to perform the functions described herein. Figures 8 to 11B One or more operations described herein. Additionally or alternatively, the apparatus 1300 may be configured to perform one or more processes described herein, such as Figure 12 The process is 1200. In some respects, Figure 13 The illustrated device 1300 and / or one or more components may include a combination Figure 2 One or more components of the described UE. Additionally or alternatively, Figure 13 One or more components shown can be combined Figure 2 Implementation within one or more of the described components. Additionally or alternatively, one or more components in the set of components may be implemented at least partially as software stored in one or more memories. For example, a component (or a portion thereof) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the function or operation of the component.

[0189] Receiver 1302 may receive communications from device 1308, such as reference signals, control information, data communications, or combinations thereof. Receiver 1302 may provide the received communications to one or more other components of device 1300. In some aspects, receiver 1302 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) and may provide the processed signals to the one or more other components of device 1300. In some aspects, receiver 1302 may include combinations of... Figure 2 The described UE includes one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receiver processors, one or more controllers / processors, one or more memories, or combinations thereof.

[0190] Transmitting component 1304 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1308. In some aspects, one or more other components of device 1300 may generate communications and provide the generated communications to transmitting component 1304 for transmission to device 1308. In some aspects, transmitting component 1304 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1308. In some aspects, transmitting component 1304 may include combinations of... Figure 2 The described UE may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or combinations thereof. In some aspects, the transmit component 1304 may co-located with the receive component 1302 in one or more transceivers.

[0191] The communication manager 1306 may support the operation of the receiving component 1302 and / or the transmitting component 1304. For example, the communication manager 1306 may receive information associated with configuring the receiving component 1302 to receive communication and / or the transmitting component 1304 to transmit communication. Additionally or alternatively, the communication manager 1306 may generate control information and / or provide control information to the receiving component 1302 and / or the transmitting component 1304 to control the receiving and / or transmitting of communication.

[0192] The receiving component 1302 can receive transmissions associated with one or more bits. The communication manager 1306 can decode the transmissions using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and an offset based at least in part on the number of one or more confidence level values.

[0193] Figure 13 The number and arrangement of components shown are provided as an example. In reality, with... Figure 13 Compared to the components shown, there may be additional components, fewer components, different components, or components arranged in a different manner. Furthermore, Figure 13 The two or more components shown can be implemented within a single component, or Figure 13 The single component shown can be implemented as multiple distributed components. Additionally or alternatively, Figure 13 The component collection shown (a collection of one or more components) can be executed as described by... Figure 13 The other set of components shown performs one or more functions.

[0194] Figure 14 This is a diagram of an example device 1400 for wireless communication according to the present disclosure. Device 1400 may be a network node, or a network node may include device 1400. In some aspects, device 1400 includes a receiving component 1402, a transmitting component 1404, and / or a communication manager 1406 that can communicate with each other (e.g., via one or more buses and / or one or more other components). In some aspects, communication manager 1406 is combined with... Figure 1 The described communication manager 150. As shown, device 1400 can communicate with another device 1408 (such as a UE or a network node (such as a CU, DU, RU or base station)) using receiving component 1402 and transmitting component 1404.

[0195] In some respects, device 1400 can be configured to perform the functions described herein. Figures 8 to 11B One or more operations described herein. Additionally or alternatively, the apparatus 1400 may be configured to perform one or more processes described herein, such as Figure 12 The process is 1200. In some respects, Figure 14 The illustrated device 1400 and / or one or more components may include a combination Figure 2 One or more components of the described network node. Additionally or alternatively, Figure 14 One or more components shown can be combined Figure 2 Implementation within one or more of the described components. Additionally or alternatively, one or more components in the set of components may be implemented at least partially as software stored in one or more memories. For example, a component (or a portion thereof) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the function or operation of the component.

[0196] Receiver 1402 may receive communications from device 1408, such as reference signals, control information, data communications, or combinations thereof. Receiver 1402 may provide the received communications to one or more other components of device 1400. In some aspects, receiver 1402 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) and may provide the processed signals to the one or more other components of device 1400. In some aspects, receiver 1402 may include combinations of... Figure 2 The described network node includes one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receiver processors, one or more controllers / processors, one or more memories, or combinations thereof.

[0197] Transmitting component 1404 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1408. In some aspects, one or more other components of device 1400 may generate communications and provide the generated communications to transmitting component 1404 for transmission to device 1408. In some aspects, transmitting component 1404 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1408. In some aspects, transmitting component 1404 may include combinations of... Figure 2 The described network node includes one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or combinations thereof. In some aspects, the transmit component 1404 may co-located with the receive component 1402 in one or more transceivers.

[0198] The communication manager 1406 may support the operation of the receiving component 1402 and / or the transmitting component 1404. For example, the communication manager 1406 may receive information associated with configuring the receiving component 1402 to receive communication and / or the transmitting component 1404 to transmit communication. Additionally or alternatively, the communication manager 1406 may generate control information and / or provide control information to the receiving component 1402 and / or the transmitting component 1404 to control the receiving and / or transmitting of communication.

[0199] The receiving component 1402 can receive transmissions associated with one or more bits. The communication manager 1406 can decode the transmissions using an average of one or more confidence level values ​​associated with one or more bits relative to the number of one or more confidence level values ​​and an offset based at least in part on the number of one or more confidence level values.

[0200] Figure 14 The number and arrangement of components shown are provided as an example. In reality, with... Figure 14 Compared to the components shown, there may be additional components, fewer components, different components, or components arranged in a different manner. Furthermore, Figure 14 The two or more components shown can be implemented within a single component, or Figure 14 The single component shown can be implemented as multiple distributed components. Additionally or alternatively, Figure 14 The component collection shown (a collection of one or more components) can be executed as described by... Figure 14 The other set of components shown performs one or more functions.

[0201] The following provides an overview of some aspects of this disclosure:

[0202] Aspect 1: A method of wireless communication performed by a wireless communication device, the method comprising: receiving a transmission associated with one or more bits; and decoding the transmission using an average of one or more confidence level values ​​associated with the one or more bits relative to a number of the one or more confidence level values ​​and an offset at least in part based on the number of the one or more confidence level values.

[0203] Aspect 2: According to the method of aspect 1, each of the one or more confidence level values ​​is equal to the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

[0204] Aspect 3: According to the method of aspect 2, wherein decoding the transmission includes using a counter to identify the one or more confidence level values.

[0205] Aspect 4: According to the method of aspect 2, decoding the transmission includes discretizing the one or more confidence level values.

[0206] Aspect 5: The method according to any one of Aspects 1 to 4, wherein the one or more confidence level values ​​are within a non-zero difference threshold from the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

[0207] Aspect 6: According to the method of aspect 5, decoding the transmission includes discretizing the average value of the one or more confidence level values.

[0208] Aspect 7: According to the method of aspect 6, discretizing the average of the one or more confidence level values ​​includes rounding the average of the one or more confidence level values ​​in a certain direction, and decoding the transmission further includes discretizing the offset by rounding the offset in the direction.

[0209] Aspect 8: The method according to any one of Aspects 1 to 7, wherein decoding the transmission includes discretizing the offset.

[0210] Aspect 9: According to the method of aspect 8, discretizing the offset includes discretizing the offset at least in part based on a lookup table.

[0211] Aspect 10: The method according to any one of Aspects 1 to 9, wherein the wireless communication device is a UE.

[0212] Aspect 11: The method according to any one of Aspects 1 to 10, wherein the wireless communication device is a network node.

[0213] Aspect 12: An apparatus for wireless communication at a device, the apparatus comprising: one or more processors; one or more memories coupled to the one or more processors; and instructions stored in the one or more memories and executable by the one or more processors to cause the apparatus to perform the method according to one or more of aspects 1 to 11.

[0214] Aspect 13: An apparatus for wireless communication at a device, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the device to perform the method according to one or more of aspects 1 to 11.

[0215] Aspect 14: An apparatus for wireless communication, the apparatus comprising at least one component for performing the method according to one or more of aspects 1 to 11.

[0216] Aspect 15: A non-transitory computer-readable medium storing code for wireless communication, said code including instructions executable by one or more processors to perform the methods described in one or more of aspects 1 to 11.

[0217] Aspect 16: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method according to one or more of aspects 1 to 11.

[0218] Aspect 17: A device for wireless communication, the device including a processing system comprising one or more processors and one or more memories coupled to the one or more processors, the processing system being configured to cause the device to perform the method according to one or more of aspects 1 to 11.

[0219] Aspect 18: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors being individually or collectively configured to cause the device to perform the method according to one or more of aspects 1 to 11.

[0220] While the foregoing disclosure provides examples and descriptions, it is not intended to be exhaustive or to limit the aspects to the precise form disclosed. Modifications and variations may be made based on the foregoing disclosure, or from various forms of practice.

[0221] As used herein, the term "component" is intended to be broadly interpreted as hardware or a combination of hardware and at least one of software or firmware. "Software" should be broadly interpreted as instructions, instruction sets, code, code segments, program code, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executable programs, threads of execution, procedures, or functions, whether referred to as software, firmware, middleware, microcode, hardware description languages, or other terms. As used herein, a "processor" is implemented in hardware or a combination of hardware and software. It will be apparent that the systems or methods described herein may be implemented in various forms of hardware or combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems or methods is not limited in any way. Therefore, the operation and behavior of these systems or methods are described herein without reference to specific software code, as those skilled in the art will understand that the software and hardware can be designed to implement these systems or methods, at least in part, based on the description herein. Unless otherwise stated, a component configured to perform a function means that the component has the capability to perform that function, but it is not necessary for the component to actually perform that function.

[0222] As used in this article, depending on the context, "meeting the threshold" can mean a value greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, not equal to the threshold, etc.

[0223] As used in this article, the phrase “at least one of” in a list of items refers to any combination of these items, including a single member. As an example, “at least one of the following: a, b, or c” is intended to cover a, b, c, a+b, a+c, b+c, and a+b+c, as well as any combination with multiple of the same element (e.g., a+a, a+a+a, a+a+b, a+a+c, a+b+b, a+c+c, b+b, b+b+b, b+b+c, c+c, and c+c+c, or any other ordering of a, b, and c).

[0224] No element, action, or instruction used herein should be construed as essential or necessary unless explicitly stated otherwise. Furthermore, as used herein, the articles “a” and “an” are intended to include one or more items and are used interchangeably with “one or more.” Similarly, as used herein, the article “described” is intended to include one or more items mentioned in connection with the article “described” and is used interchangeably with “one or more.” Furthermore, as used herein, the terms “set” and “group” are intended to include one or more items and are used interchangeably with “one or more.” If only one item is desired, the phrase “only one” or similar terminology will be used. Moreover, as used herein, the terms “having” and similar terms are intended as open-ended terms that do not limit the elements they modify (e.g., “having” A may also have B). Additionally, the phrase “based on” is intended to mean “based on or otherwise related to” unless otherwise explicitly stated. Furthermore, as used herein, the term “or” is intended to be inclusive when used consecutively and is interchangeable with “and / or” unless otherwise explicitly stated (e.g., if used in conjunction with “either of the two” or “only one of them”). It should be understood that “one or more” is equivalent to “at least one”.

[0225] Although specific combinations of features are set forth in the claims or disclosed in the description, these combinations are not intended to limit the disclosure of various aspects. Many of these features may be combined in ways not specifically stated in the claims or disclosed in the description. The disclosure of various aspects includes each dependent claim in combination with each other claim in the claim set.

Claims

1. An apparatus for performing wireless communication at a wireless communication device, the apparatus comprising: One or more memory units; and One or more processors, said one or more processors being coupled to said one or more memories and being individually or collectively configured to enable the wireless communication device to: Receive transmissions associated with one or more bits; and The transmission is decoded using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of the one or more confidence level values ​​and an offset at least in part based on the number of the one or more confidence level values.

2. The apparatus of claim 1, wherein each of the one or more confidence level values ​​is equal to the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

3. The apparatus of claim 2, wherein, in order for the wireless communication device to decode the transmission, the one or more processors are configured to cause the wireless communication device to use a counter to identify the one or more confidence level values.

4. The apparatus of claim 2, wherein, in order for the wireless communication device to decode the transmission, the one or more processors are configured to cause the wireless communication device to discretize the one or more confidence level values.

5. The apparatus of claim 1, wherein the one or more confidence level values ​​are within a non-zero difference threshold from the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

6. The apparatus of claim 5, wherein, in order for the wireless communication device to decode the transmission, the one or more processors are configured to cause the wireless communication device to discretize the average value of the one or more confidence levels.

7. The apparatus of claim 6, wherein, in order for the wireless communication device to discretize the average value of the one or more confidence levels, the one or more processors are configured to cause the wireless communication device to round the average value of the one or more confidence levels in a certain direction, and wherein, in order for the wireless communication device to decode the transmission, the one or more processors are further configured to cause the wireless communication device to discretize the offset by rounding the offset in the direction.

8. The apparatus of claim 1, wherein, in order for the wireless communication device to decode the transmission, the one or more processors are configured to cause the wireless communication device to discretize the offset.

9. The apparatus of claim 8, wherein, in order for the wireless communication device to discretize the offset, the one or more processors are configured to cause the wireless communication device to discretize the offset at least in part based on a lookup table.

10. The apparatus of claim 1, wherein the wireless communication device is a user equipment (UE).

11. The apparatus of claim 1, wherein the wireless communication device is a network node.

12. A method for wireless communication performed by a wireless communication device, the method comprising: Receive a transmission associated with one or more bits; as well as The transmission is decoded using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of the one or more confidence level values ​​and an offset at least in part based on the number of the one or more confidence level values.

13. The method of claim 12, wherein each of the one or more confidence level values ​​is equal to the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

14. The method of claim 13, wherein decoding the transmission includes using a counter to identify the one or more confidence level values.

15. The method of claim 13, wherein decoding the transmission includes discretizing the one or more confidence level values.

16. The method of claim 12, wherein decoding the transmission includes discretizing the offset.

17. A non-transitory computer-readable medium storing an instruction set for wireless communication, the instruction set comprising: One or more instructions, which, when executed by one or more processors of a wireless communication device, cause the wireless communication device to: Receive transmissions associated with one or more bits; and The transmission is decoded using an average of one or more confidence level values ​​associated with the one or more bits relative to the number of the one or more confidence level values ​​and an offset at least in part based on the number of the one or more confidence level values.

18. The non-transitory computer-readable medium of claim 17, wherein the one or more confidence level values ​​are within a non-zero difference threshold from the minimum of a plurality of confidence level values ​​including the one or more confidence level values.

19. The non-transitory computer-readable medium of claim 18, wherein the one or more instructions that cause the wireless communication device to decode the transmission cause the wireless communication device to discretize the average value of the one or more confidence level values.

20. The non-transitory computer-readable medium of claim 19, wherein the one or more instructions causing the wireless communication device to discretize the average of the one or more confidence levels cause the wireless communication device to round the average of the one or more confidence levels in a certain direction, and wherein the one or more instructions causing the wireless communication device to decode the transmission further cause the wireless communication device to discretize the offset by rounding the offset in the direction.

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