Method and communication device for performing decoding, processing device, and storage medium

Abstract

This communication device may: receive a signal and acquire a first bit sequence having a length of N from the received signal; generate P number of second bit sequences by applying P number of different permutations to the first bit sequence; and complete decoding only for each of Lc number of second bit sequences having uppermost minimum log likelihood ratio (LLR) values that are greater than a predetermined second threshold value among the P number of second bit sequences.

Description

Method for performing decoding, communication device, processing device, and storage medium

[0001] This specification relates to wireless communication systems.

[0002] Various devices and technologies, such as machine-to-machine (M2M) communication, machine-type communication (MTC), and smartphones and tablet PCs (personal computers) that require high data transmission rates, are emerging and becoming widespread. Consequently, the amount of data required to be processed on cellular networks is rapidly increasing. To meet this rapidly increasing data processing demand, technologies such as carrier aggregation and cognitive radio are being developed to efficiently utilize more frequency bands, while multi-antenna technology and multi-BS cooperation technology are being developed to increase the data capacity transmitted within a limited frequency range.

[0003] As more and more communication devices demand greater capacity, the need for enhanced mobile broadband (eMBB) communications is emerging, surpassing legacy radio access technology (RAT). Furthermore, massive machine type communication (mMTC), which connects multiple devices and objects to provide diverse services anytime, anywhere, is a key issue to be considered in next-generation communications.

[0004] Additionally, discussions are underway on communication systems designed to accommodate reliability- and latency-sensitive services and user equipment (UE). The introduction of next-generation wireless access technologies is being discussed, including enhanced mobile broadband (eMBB), mMTC, and ultra-reliable and low latency communication (URLLC).

[0005] There is a need to further improve the performance of polar codes, which have been proposed as alternatives to existing channel codes. For example, the list successive cancellation decoder used in conventional polar code decoding has significant implementation complexity and delay due to the alignment operation performed on each bit. Therefore, a solution to address these issues is needed.

[0006] The technical tasks that this specification aims to achieve are not limited to the technical tasks mentioned above, and other technical tasks that are not mentioned will be clearly understood by those skilled in the art related to this specification from the detailed description below.

[0007] In one aspect of the present disclosure, a method for decoding a received signal by a communication device in a wireless communication system is provided. The method may include: receiving a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; obtaining a first bit sequence of length N from the bit sequence y; applying P different permutations to the first bit sequence to generate P second bit sequences, where P is an integer greater than 1; performing successive erasure decoding based on the P second bit sequences; and determining a codeword based on the successive erasure decoding. The successive erasure decoding may include: selecting, from among the P second bit sequences, LLR values ​​having top minimum log likelihood ratio (LLR) values ​​greater than a predetermined second threshold τ2. c Completing decoding only for each of the second bit sequences, where L c is a positive integer less than P.

[0008] In another aspect of the present disclosure, a communication device for decoding a received signal in a wireless communication system is provided. The communication device comprises: at least one transceiver; at least one processor; and at least one computer memory operably connected to the at least one processor and storing instructions that, when executed, cause the at least one processor to perform operations, wherein the operations may include: receiving a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; obtaining a first bit sequence of length N from the bit sequence y; applying P different permutations to the first bit sequence to generate P second bit sequences, where P is an integer greater than 1; performing successive erasure decoding based on the P second bit sequences; and determining a codeword based on the successive erasure decoding. The above continuous erasure decoding is: among the P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values ​​greater than a predetermined second threshold τ2. c Completing decoding only for each of the second bit sequences, where L c is a positive integer less than P.

[0009] In another aspect of the present disclosure, a processing device is provided. The processing device includes: at least one processor; and at least one computer memory operably connected to the at least one processor and storing instructions that, when executed, cause the at least one processor to perform operations, wherein the operations may include: receiving a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; obtaining a first bit sequence of length N from the bit sequence y; applying P different permutations to the first bit sequence to generate P second bit sequences, where P is an integer greater than 1; performing successive erasure decoding based on the P second bit sequences; and determining a codeword based on the successive erasure decoding. The above continuous erasure decoding is: among the P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values ​​greater than a predetermined second threshold τ2. c Completing decoding only for each of the second bit sequences, where L c is a positive integer less than P.

[0010] In another aspect of the present disclosure, a computer-readable storage medium is provided. The storage medium stores at least one program code comprising instructions that, when executed, cause at least one processor to perform operations, the operations including: receiving a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; obtaining a first bit sequence of length N from the bit sequence y; applying P different permutations to the first bit sequence to generate P second bit sequences, where P is an integer greater than 1; performing successive erasure decoding based on the P second bit sequences; and determining a codeword based on the successive erasure decoding. The successive erasure decoding may include: determining, from among the P second bit sequences, LLR values ​​having top minimum log likelihood ratio (LLR) values ​​greater than a predetermined second threshold τ2. c Completing decoding only for each of the second bit sequences, where L c is a positive integer less than P.

[0011] In each aspect of this specification, the successive erasure decoding is performed if: i) the minimum LLR value among the LLR values ​​of the least reliable t information bits is not greater than τ2, or ii) the L c It may include terminating before completing decoding for a second bit sequence that does not belong to the second bit sequences.

[0012] In each aspect of the present specification, the successive erasure decoding may include: terminating decoding for a second bit sequence having an information bit having an LLR value less than a predefined first threshold τ1 among the P second bit sequences at the information bit having the LLR value less than τ1.

[0013] In each aspect of the present specification, the successive erasure decoding may include: comparing the LLR values ​​of the least reliable t information bits in each of the P second bit sequences with τ1; and terminating the decoding for the second bit sequence at an information bit among the least reliable t information bits having an LLR value less than τ1.

[0014] In each aspect of the present specification, the encoded bit sequence may be obtained based on the polar code having K information bits and a size of N.

[0015] In each aspect of the present specification, it may include determining an information bit sequence of length K based on a polar sequence of length N that sorts the N bit indices of the codeword and the polar code of length N according to reliability.

[0016] In each aspect of this specification, the successive erasure decoding: the L c L based on the second bit sequences of the dog c Output the third bit sequences; and the L c It may include outputting, as the codeword, a bit sequence that minimizes the distance between the bit sequence y and the third bit sequence among the third bit sequences.

[0017] The above problem solving methods are only some of the examples of this specification, and various examples reflecting the technical features of this specification can be derived and understood by a person having ordinary knowledge in the relevant technical field based on the detailed description below.

[0018] According to some implementations of this specification, wireless communication signals can be transmitted / received efficiently. Consequently, the overall throughput of a wireless communication system can be increased.

[0019] Some implementations of this specification may enable parallel decoding of polar codes. This may overcome the drawback of existing polar code decoding methods, which increase implementation difficulty due to the complexity of metric sorting.

[0020] According to some implementation(s) of this specification, the shortcomings of permutation decoding can be overcome.

[0021] The effects according to this specification are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art related to this specification from the detailed description below.

[0022] To aid in understanding implementations of this specification, the accompanying drawings, which are included as part of the detailed description, provide examples of implementations of this specification and, together with the detailed description, illustrate implementations of this specification:

[0023] Figure 1 illustrates an example of a communication system 1 to which implementations of the present specification are applied;

[0024] FIG. 2 is a block diagram illustrating examples of communication devices capable of performing a method according to the present specification.

[0025] FIG. 3 illustrates another example of a wireless device capable of performing implementation(s) of this specification;

[0026] Figure 4 is the 3rd generation partnership project (3 rd It illustrates an example of a frame structure available in a wireless communication system based on the 3rd Generation Partnership Project (3GPP);

[0027] Figure 5 illustrates a processing process on the transmission side for a transport block (TB);

[0028] Figure 6 is an example of a block diagram for a polar encoder;

[0029] Figure 7 illustrates the concept of channel combining and channel splitting for channel polarization;

[0030] Fig. 8 illustrates N-th level channel combining for polar code;

[0031] Figure 9 illustrates the evolution of decoding paths in the List-L decoding process;

[0032] FIG. 10 is a diagram illustrating the concept of selecting the location(s) to which information bit(s) are to be allocated in a polar code;

[0033] Figure 11 illustrates puncturing and information bit allocation for a polar code;

[0034] Fig. 12 is an example of a permutation decoder;

[0035] FIG. 13 is a diagram illustrating an example of a decoding process according to some implementations of the present specification;

[0036] FIG. 14 is a diagram illustrating another example of a decoding process according to some implementations of the present specification;

[0037] Figure 15 shows the changes in the minimum log likelihood ratio (LLR) values ​​of each decoding path in sequential decoding according to bit indices;

[0038] FIGS. 16 and 17 are illustrations to illustrate a method for determining the size of a test area according to some implementations of the present specification;

[0039] Figures 18 to 23 present the error probability of each bit for each code structure;

[0040] FIGS. 24 and 25 illustrate the word error ratio (WER) and complexity performance of decoding schemes according to some implementations of the present specification;

[0041] Figure 26 illustrates another decoding process in some implementations of this specification;

[0042] Figure 27 illustrates physical channels used in a 3GPP-based communication system, which is an example of a wireless communication system, and a signal transmission / reception process using the channels;

[0043] Figure 28 illustrates a random access process that may be applied to implementation(s) of this specification.

[0044] Hereinafter, implementations according to this specification will be described in detail with reference to the attached drawings. The detailed description provided below, together with the attached drawings, is intended to describe exemplary implementations of this specification and is not intended to represent the only possible implementations of this specification. The detailed description below includes specific details to provide a thorough understanding of this specification. However, one of ordinary skill in the art will appreciate that this specification may be practiced without these specific details.

[0045] In some cases, to avoid ambiguity in the concepts of this specification, known structures and devices may be omitted or illustrated in block diagram form focusing on the core functions of each structure and device. Furthermore, identical components are described using the same drawing reference numerals throughout this specification.

[0046] The techniques, devices, and systems described below can be applied to various wireless multiple access systems. Examples of multiple access systems include code division multiple access (CDMA) systems, frequency division multiple access (FDMA) systems, time division multiple access (TDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single carrier frequency division multiple access (SC-FDMA) systems, and multi-carrier frequency division multiple access (MC-FDMA) systems. CDMA can be implemented in wireless technologies such as Universal Terrestrial Radio Access (UTRA) or CDMA2000. TDMA can be implemented in wireless technologies such as Global System for Mobile communication (GSM), General Packet Radio Service (GPRS), and Enhanced Data Rates for GSM Evolution (EDGE) (i.e., GERAN). OFDMA can be implemented in wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (WiFi), IEEE 802.16 (WiMAX), IEEE 802-20, and E-UTRA (evolved-UTRA). UTRA is part of UMTS (Universal Mobile Telecommunication System), and 3GPP (3rd Generation Partnership Project) LTE (Long Term Evolution) is a part of E-UMTS that uses E-UTRA.3GPP LTE adopts OFDMA for the downlink (DL) and SC-FDMA for the uplink (UL). LTE-A (LTE-advanced) is an evolved form of 3GPP LTE.

[0047] For convenience of explanation, the following description assumes that this specification applies to 3GPP-based communication systems, such as LTE and NR. However, the technical features of this specification are not limited to this. For example, although the detailed description below is based on a mobile communication system corresponding to a 3GPP LTE / NR system, it can also be applied to any other mobile communication system, except for features specific to 3GPP LTE / NR.

[0048] For terms and technologies used in this specification that are not specifically explained, reference may be made to 3GPP-based standard documents, such as 3GPP TS 36.211, 3GPP TS 36.212, 3GPP TS 36.213, 3GPP TS 36.321, 3GPP TS 36.300 and 3GPP TS 36.331, 3GPP TS 37.213, 3GPP TS 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.214, 3GPP TS 38.300, 3GPP TS 38.331, etc.

[0049] In the examples of this specification described below, the expression "assumes" that a device "assumes" that the entity transmitting the channel transmits the channel in a manner consistent with the "assume." The entity receiving the channel may mean that, under the assumption that the channel was transmitted in a manner consistent with the "assume," the entity receiving the channel receives or decodes the channel in a manner consistent with the "assume."

[0050] In this specification, UE may be fixed or mobile, and includes various devices that communicate with a BS (base station) to transmit and / or receive user data and / or various control information. UE may be called (Terminal Equipment), MS (Mobile Station), MT (Mobile Terminal), UT (User Terminal), SS (Subscribe Station), wireless device, PDA (Personal Digital Assistant), wireless modem, handheld device, etc. In addition, in this specification, BS generally refers to a fixed station that communicates with UE and / or other BS, and exchanges various data and control information with UE and other BS. BS may be called by other terms such as ABS (Advanced Base Station), NB (Node-B), eNB (evolved-NodeB), BTS (Base Transceiver System), Access Point, PS (Processing Server), etc. In particular, the BS in UTRAN is called a Node-B, the BS in E-UTRAN is called an eNB, and the BS in a new radio access technology network is called a gNB. For convenience of explanation, BSs are collectively referred to as BSs below, regardless of the type or version of communication technology.

[0051] In this specification, a node refers to a fixed point that can transmit / receive radio signals by communicating with a UE. Various types of BSs can be used as nodes regardless of their names. For example, BSs, NBs, eNBs, pico-cell eNBs (PeNBs), home eNBs (HeNBs), relays, and repeaters can be nodes. Furthermore, a node may not be a BS. For example, it can be a radio remote head (RRH) or a radio remote unit (RRU). RRHs, RRUs, etc. generally have a lower power level than the BS. Since an RRH or RRU (hereinafter referred to as RRH / RRU) is generally connected to a BS via a dedicated line such as an optical cable, cooperative communication between an RRH / RRU and a BS can be performed more smoothly than cooperative communication between BSs that are generally connected via a wireless line. Each node is equipped with at least one antenna. The antenna may be a physical antenna, an antenna port, a virtual antenna, or an antenna group. A node is also called a point.

[0052] In this specification, a cell refers to a certain geographical area where one or more nodes provide communication services. Therefore, in this specification, communicating with a specific cell may mean communicating with a BS or node that provides communication services to the specific cell. In addition, the downlink / uplink signal of a specific cell refers to a downlink / uplink signal from / to a BS or node that provides communication services to the specific cell. A cell that provides uplink / downlink communication services to a UE is specifically referred to as a serving cell. In addition, the channel state / quality of a specific cell refers to the channel state / quality of a channel or communication link formed between a BS or node that provides communication services to the specific cell and the UE. In a 3GPP-based communication system, a UE can measure a downlink channel state from a specific node using CRS (Cell-specific Reference Signal) resources transmitted by antenna port(s) of the specific node on CRS resources allocated to the specific node and / or CSI-RS (Channel State Information Reference Signal) resources transmitted.

[0053] Meanwhile, 3GPP-based communication systems use the concept of cells to manage radio resources, and cells associated with radio resources are distinguished from cells in geographical areas.

[0054] A "cell" in a geographical area can be understood as the coverage over which a node can provide a service using a carrier, and a "cell" in a radio resource is associated with a bandwidth (BW), which is a frequency range configured by the carrier. Since downlink coverage, which is the range over which a node can transmit a valid signal, and uplink coverage, which is the range over which a node can receive a valid signal from a UE, depend on the carrier carrying the signal, the coverage of a node is also associated with the coverage of the "cell" of the radio resource used by the node. Therefore, the term "cell" can sometimes be used to mean the coverage of a service provided by a node, sometimes a radio resource, and sometimes the range over which a signal using the radio resource can reach with a valid intensity.

[0055] Meanwhile, the 3GPP communication standard uses the concept of a cell to manage radio resources. A "cell" associated with radio resources is defined as a combination of downlink resources (DL resources) and uplink resources (UL resources), i.e., a combination of a DL component carrier (CC) and an UL CC. A cell can be configured with DL resources alone or a combination of DL resources and UL resources. If carrier aggregation is supported, the linkage between the carrier frequency of the DL resources (or DL ​​CC) and the carrier frequency of the UL resources (or UL CC) can be indicated by system information. For example, the combination of DL resources and UL resources can be indicated by a System Information Block Type 2 (SIB2) linkage. Here, the carrier frequency can be the same as or different from the center frequency of each cell or CC. When carrier aggregation (CA) is established, the UE has only one radio resource control (RRC) connection with the network. One serving cell provides non-access stratum (NAS) mobility information during RRC connection establishment / re-establishment / handover, and one serving cell provides security input during RRC connection re-establishment / handover. Such a cell is called a primary cell (Pcell). A Pcell is a cell operating on the primary frequency where the UE performs initial connection establishment procedures or initiates connection re-establishment procedures.Depending on the UE capability, secondary cells (Scells) can be configured to form a set of serving cells together with Pcells. An Scell ​​can be configured after RRC (Radio Resource Control) connection establishment, and is a cell that provides additional radio resources in addition to the resources of a special cell (SpCell). The carrier corresponding to a Pcell in downlink is called a downlink primary CC (DL PCC), and the carrier corresponding to a Pcell in uplink is called an UL primary CC (DL PCC). The carrier corresponding to an Scell ​​in downlink is called a DL secondary CC (DL SCC), and the carrier corresponding to the Scell ​​in uplink is called an UL secondary CC (UL SCC).

[0056] As more and more communication devices demand greater communication capacity, the need for improved mobile broadband communication over existing radio access technology (RAT) is emerging. Furthermore, massive MTC, which connects numerous devices and objects to provide diverse services anytime, anywhere, is also a key issue to be considered in next-generation communications. Furthermore, communication system design that considers reliability and latency-sensitive services / UEs is being discussed. The introduction of next-generation RATs that take advanced mobile broadband communication, massive MTC, and URLLC (Ultra-Reliable and Low Latency Communication) into account is currently under discussion. 3GPP is currently conducting studies on next-generation mobile communication systems beyond EPC. For convenience, this technology is referred to as new RAT (NR) or 5G RAT, and a system that uses or supports NR is referred to as an NR system.

[0057] FIG. 1 illustrates an example of a communication system 1 to which implementations of the present specification are applied. Referring to FIG. 1, the communication system (1) applied to the present specification includes a wireless device, a BS, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR (New RAT), LTE (e.g., E-UTRA)) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI device / server (400). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicle may include an Unmanned Aerial Vehicle (UAV) (e.g., a drone). XR devices include AR (Augmented Reality) / VR (Virtual Reality) / MR (Mixed Reality) devices, and may be implemented in the form of a Head-Mounted Device (HMD), a Head-Up Display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc. Mobile devices may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. Home appliances may include a TV, a refrigerator, a washing machine, etc. IoT devices may include sensors, smart meters, etc. For example, a BS or network may also be implemented as a wireless device, and a specific wireless device may act as a BS / network node to other wireless devices.

[0058] Wireless devices (100a to 100f) can be connected to a network (300) via a BS (200). Artificial Intelligence (AI) technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (400) via a network (300). The network (300) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, etc. The wireless devices (100a to 100f) can communicate with each other via the BS (200) / network (300), but can also communicate directly (e.g., sidelink communication) without going through the BS / network. For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (Vehicle to Vehicle) / V2X (Vehicle to Everything) communication). In addition, IoT devices (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0059] Wireless communication / connection (150a, 150b) can be performed between wireless devices (100a~100f) / BS (200) - BS (200) / wireless devices (100a~100f). Here, the wireless communication / connection can be performed through various wireless access technologies (e.g., 5G NR) for uplink / downlink communication (150a) and sidelink communication (150b) (or D2D communication). Through the wireless communication / connection (150a, 150b), the wireless device and the BS / wireless device can transmit / receive wireless signals to / from each other. To this end, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), and resource allocation processes can be performed based on various proposals of this specification.

[0060] FIG. 2 is a block diagram illustrating examples of communication devices capable of performing a method according to the present specification. Referring to FIG. 2, a first wireless device (100) and a second wireless device (200) can transmit and / or receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (100), the second wireless device (200)} can correspond to {the wireless device (100x), the BS (200)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 1.

[0061] A first wireless device (100) includes one or more processors (102) and one or more memories (104), and may further include one or more transceivers (106) and / or one or more antennas (108). The processor (102) controls the memories (104) and / or the transceivers (106), and may be configured to implement functions, procedures, and / or methods described / suggested below. For example, the processor (102) may process information in the memory (104) to generate first information / signals, and then transmit a wireless signal including the first information / signals via the transceivers (106). In addition, the processor (102) may receive a wireless signal including second information / signals via the transceivers (106), and then store information obtained from signal processing of the second information / signals in the memory (104). The memory (104) may be connected to the processor (102) and may store various information related to the operation of the processor (102). For example, the memory (104) may perform some or all of the processes controlled by the processor (102), or may store software code including commands for performing the procedures and / or methods described / proposed below. Here, the processor (102) and the memory (104) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals via one or more antennas (108). The transceiver (106) may include a transmitter and / or a receiver. The transceiver (106) may be used interchangeably with an RF (Radio Frequency) unit. In this specification, a wireless device may also mean a communication modem / circuit / chip.

[0062] The second wireless device (200) includes one or more processors (202), one or more memories (204), and may further include one or more transceivers (206) and / or one or more antennas (208). The processor (202) controls the memories (204) and / or the transceivers (206), and may be configured to implement the functions, procedures, and / or methods described / suggested below. For example, the processor (202) may process information in the memory (204) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206). In addition, the processor (202) may receive a wireless signal including fourth information / signals via the transceivers (206), and then store information obtained from signal processing of the fourth information / signals in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may perform some or all of the processes controlled by the processor (202), or may store software code including commands for performing the procedures and / or methods described / proposed below. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via one or more antennas (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF unit. In this specification, a wireless device may also mean a communication modem / circuit / chip.

[0063] The wireless communication technology implemented in the wireless device (100, 200) of the present specification may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. At this time, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless device (XXX, YYY) of the present specification may perform communication based on LTE-M technology. At this time, for example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless device (XXX, YYY) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create PAN (personal area networks) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0064] Hereinafter, hardware elements of the wireless device (100, 200) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (102, 202). For example, one or more processors (102, 202) may implement one or more layers (e.g., functional layers such as a physical (PHY) layer, a medium access control (MAC) layer, a radio link control (RLC) layer, a packet data convergence protocol (PDCP) layer, a radio resource control (RRC) layer, and a service data adaptation protocol (SDAP) layer). One or more processors (102, 202) may generate one or more protocol data units (PDUs) and / or one or more service data units (SDUs) according to the functions, procedures, proposals, and / or methods disclosed in this specification. One or more processors (102, 202) may generate messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this specification. One or more processors (102, 202) may generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this specification, and provide the signals to one or more transceivers (106, 206). One or more processors (102, 202) may receive signals (e.g., baseband signals) from one or more transceivers (106, 206) and obtain PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this specification.

[0065] One or more processors (102, 202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (102, 202) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Digital Signal Processing Devices (DSPDs), one or more Programmable Logic Devices (PLDs), or one or more Field Programmable Gate Arrays (FPGAs) may be included in one or more processors (102, 202). The functions, procedures, proposals, and / or methods disclosed in this specification may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. Firmware or software configured to perform the functions, procedures, suggestions and / or methods disclosed in this specification may be included in one or more processors (102, 202) or stored in one or more memories (104, 204) and executed by one or more processors (102, 202). The functions, procedures, suggestions and / or methods disclosed in this specification may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0066] One or more memories (104, 204) may be coupled to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (104, 204) may be configured as ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media, and / or combinations thereof. The one or more memories (104, 204) may be located internally and / or externally to the one or more processors (102, 202). Additionally, the one or more memories (104, 204) may be coupled to the one or more processors (102, 202) via various technologies, such as wired or wireless connections.

[0067] One or more transceivers (106, 206) may transmit user data, control information, wireless signals / channels, etc., as described in the methods and / or flowcharts of this specification, to one or more other devices. One or more transceivers (106, 206) may receive user data, control information, wireless signals / channels, etc., as described in the functions, procedures, proposals, methods and / or flowcharts of this specification, from one or more other devices. For example, one or more transceivers (106, 206) may be coupled to one or more processors (102, 202) and may transmit and / or receive wireless signals. For example, one or more processors (102, 202) may control one or more transceivers (106, 206) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (102, 202) may control one or more transceivers (106, 206) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (106, 206) may be coupled to one or more antennas (108, 208), and one or more transceivers (106, 206) may be configured to transmit and / or receive user data, control information, wireless signals / channels, or the like, as referred to in the functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this specification, via one or more antennas (108, 208). In this specification, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (106, 206) may convert received user data, control information, wireless signals / channels, etc. from RF band signals to baseband signals for processing using one or more processors (102, 202).One or more transceivers (106, 206) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (102, 202) from baseband signals to RF band signals. For this purpose, one or more transceivers (106, 206) may include an (analog) oscillator and / or filter.

[0068] FIG. 3 illustrates another example of a wireless device capable of performing implementation(s) of the present specification. Referring to FIG. 3, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 2 and may be composed of various elements, components, units, and / or modules. For example, the wireless device (100, 200) may include a communication unit (110), a control unit (120), a memory unit (130), and an additional component (140). The communication unit may include a communication circuit (112) and a transceiver(s) (114). For example, the communication circuit (112) may include one or more processors (102, 202) and / or one or more memories (104, 204) of FIG. 2. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 2. The control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and the additional components (140) and controls the overall operation of the wireless device. For example, the control unit (120) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (130). In addition, the control unit (120) may transmit information stored in the memory unit (130) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (110), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (130).

[0069] The additional configuration (140) may be configured in various ways depending on the type of the wireless device. For example, the additional configuration (140) may include at least one of a power unit / battery, an input / output (I / O) unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a UE for digital broadcasting, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 1, 400), a BS (Fig. 1, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0070] In FIG. 3, various elements, components, units / parts, and / or modules within the wireless device (100, 200) may be interconnected entirely via a wired interface, or at least some may be wirelessly connected via a communication unit (110). For example, within the wireless device (100, 200), the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and a first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110). In addition, each element, component, unit / part, and / or module within the wireless device (100, 200) may further include one or more elements. For example, the control unit (120) may be configured with one or more processor sets. For example, the control unit (120) may be configured as a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be configured as a random access memory (RAM), a dynamic RAM (DRAM), a read only memory (ROM), a flash memory, a volatile memory, a non-volatile memory, and / or a combination thereof.

[0071] In this specification, at least one memory (e.g., 104 or 204) can store instructions or programs that, when executed, cause at least one processor operably connected to the at least one memory to perform operations according to some embodiments or implementations of the present specification.

[0072] In this specification, a computer-readable (non-volatile) storage medium can store at least one instruction or computer program, which when executed by at least one processor causes the at least one processor to perform operations according to some embodiments or implementations of this specification.

[0073] In this specification, a processing device or apparatus may include at least one processor and at least one computer memory operatively connected to the at least one processor. The at least one computer memory may store instructions or programs, which, when executed, cause at least one processor operatively connected to the at least one memory to perform operations according to some embodiments or implementations of the present specification.

[0074] In this specification, a computer program may be stored in at least one computer-readable (non-volatile) storage medium and may include program code that, when executed, performs operations according to some implementations of the present specification or causes at least one processor to perform operations according to some implementations of the present specification. The computer program may be provided in the form of a computer program product. The computer program product may include at least one computer-readable (non-volatile) storage medium.

[0075] A communications device of the present specification comprises at least one processor; and at least one computer memory operably connected to said at least one processor and storing instructions that, when executed, cause said at least one processor to perform operations according to the example(s) of the present specification described below.

[0076] Figure 4 illustrates an example of a frame structure available in a 3GPP-based wireless communication system.

[0077] The structure of the frame in Fig. 4 is merely an example, and the number of subframes, the number of slots, and the number of symbols in the frame can be varied. In an NR system, OFDM numerology (e.g., subcarrier spacing (SCS)) may be set differently between multiple cells aggregated to a single UE. Accordingly, the (absolute time) duration of a time resource (e.g., a subframe, a slot, or a transmission time interval (TTI)) consisting of the same number of symbols may be set differently between the aggregated cells. Here, the symbol may include an OFDM symbol (or a cyclic prefix - orthogonal frequency division multiplexing (CP-OFDM) symbol), an SC-FDMA symbol (or a discrete Fourier transform-spread-OFDM (DFT-s-OFDM) symbol). In this specification, the terms symbol, OFDM-based symbol, OFDM symbol, CP-OFDM symbol, and DFT-s-OFDM symbols are interchangeable.

[0078] Referring to Figure 4, in the NR system, uplink and downlink transmissions are organized into frames. Each frame is T f = (△f max *N f / 100)*T c = 10 ms duration, divided into two half-frames of 5 ms each. Here, T is the basic time unit for NR. c = 1 / (△fmax *N f ) and △f max = 480*10 3 Hz, and N f =4096. For reference, T is the basic time unit for LTE. s = 1 / (△f ref *N f,ref ) and △f ref = 15*10 3 Hz, and N f,ref =2048. T c Wow T f is a constant κ = T c / T f = 64 relationship. Each half-frame consists of 5 subframes, and the duration of a single subframe (SF) is T sf is 1ms. Subframes are further divided into slots, and the number of slots in a subframe depends on the subcarrier spacing. Each slot consists of 14 or 12 OFDM symbols based on the cyclic prefix. For a normal cyclic prefix (CP), each slot consists of 14 OFDM symbols, and for an extended CP, each slot consists of 12 OFDM symbols. The numerology is exponentially scalable with a subcarrier spacing △f = 2. u *Depends on 15 kHz. The following table shows the subcarrier spacing for regular CP △f = 2. u *Number of OFDM symbols per slot at 15 kHz (N) slot symb ), number of slots per frame (N frame,u slot ) and the number of slots per subframe (N subframe,u slot ) is shown.

[0079]

[0080] The following table shows the subcarrier spacing for extended CP △f = 2.u *Indicates the number of OFDM symbols per slot, the number of slots per frame, and the number of slots per subframe at 15 kHz.

[0081]

[0082] For a subcarrier spacing setting u, slots are n in increasing order within a subframe. u s ∈ {0, ..., nsubframe,u slot - 1} and n in increasing order within the frame u s,f ∈ {0, ..., n frame,u slot - Numbered as 1}.

[0083] A slot contains multiple (e.g., 14 or 12) symbols in the time domain. For each numeral (e.g., subcarrier spacing) and carrier, a common resource block (CRB) N is indicated by higher-layer signaling (e.g., radio resource control (RRC) signaling). start,u grid Starting from,N size,u grid,x *N RB sc Dog subcarriers and N subframe,u symb A resource grid of OFDM symbols is defined, where N size,u grid,x is the number of resource blocks (RBs) in the resource grid, and the subscript x is DL for downlink and UL for uplink. N RB sc is the number of subcarriers per RB, and in 3GPP-based wireless communication systems, N RB scis typically 12. For a given antenna port p, subcarrier spacing configuration u, and transmission direction (DL or UL), there is one resource grid. The carrier bandwidth N for subcarrier spacing configuration u size,u grid is given to the UE by higher layer parameters (e.g., RRC parameters) from the network. Each element in the resource grid for antenna port p and subcarrier spacing configuration u is called a resource element (RE), and one complex symbol can be mapped to each RE. Each RE in the resource grid is uniquely identified by an index k in the frequency domain and an index l indicating the symbol position relative to a reference point in the time domain. In an NR system, an RB is defined by 12 consecutive subcarriers in the frequency domain. In an NR system, RBs can be classified into common resource blocks (CRBs) and physical resource blocks (PRBs). CRBs are numbered upwards from 0 in the frequency domain for the subcarrier spacing configuration u. The center of subcarrier 0 of CRB 0 for the subcarrier spacing configuration u coincides with 'Point A', which is a common reference point for the resource block grids. PRBs for subcarrier spacing u are defined within the bandwidth part (BWP) and range from 0 to N. size,u BWP,i -1, where i is the number of the bandwidth part. Common resource block n u CRB and bandwidth part i within physical resource block n PRB The relationship between the two is as follows: n u PRB = n u CRB +N start,u BWP,i , here N start,u BWP,iis a common resource block (BRB) whose bandwidth part starts relative to CRB 0. A BWP comprises multiple consecutive RBs in the frequency domain. For example, a BWP may be a given numeral u within a BWP i on a given carrier. i A subset of contiguous CRBs defined for a carrier. A carrier may include up to N (e.g., 5) BWPs. A UE may be configured to have one or more BWPs on a given component carrier. Data communication is performed through the activated BWPs, and only a predetermined number (e.g., 1) of BWPs configured for the UE may be activated on the carrier.

[0084] Figure 5 illustrates a processing process on the transmission side for a transport block (TB).

[0085] To enable the receiver to correct errors encountered in wireless signals over the wireless channel, the transmitter encodes the information it sends using a forward error correction code before transmitting it. The receiver demodulates the received signal and then decodes the error correction code to restore the transmitted information. This decoding process corrects errors in the received signal caused by the wireless channel.

[0086] Data arrives at the coding block in the form of up to two transport blocks per TTI per DL / UL cell. The following coding steps can be applied to each transport block in a DL / UL cell:

[0087] - Add a cyclic redundancy check (CRC) to the transport block;

[0088] - Code block segmentation and code block CRC attachment;

[0089] - Channel coding;

[0090] - Rate matching;

[0091] - Code block concatenation.

[0092] In actual communication systems, for ease of implementation, transport blocks larger than a certain size are divided into several smaller data blocks for encoding. These smaller data blocks are called code blocks. While code blocks generally have the same size, due to the size limitations of the channel encoder's internal interleaver, one code block among multiple code blocks may have a different size. After error correction coding is performed on each code block of a given interleaver size, interleaving is performed to reduce the impact of burst errors that occur during transmission over a wireless channel. The data is then mapped to actual radio resources and transmitted. Since the amount of radio resources used in actual transmission is constant, rate matching must be performed on the encoded code blocks to accommodate this. Rate matching is typically achieved through puncturing or repetition. For example, if the amount of wireless resources, i.e., the number of transmission bits that can be transmitted by the wireless resources, is M, and the coded bit sequence, i.e., the number of output bits of the encoder, is N, then if M and N are different, rate matching is performed to adjust the length of the coded bit sequence to match M. If M>N, all or part of the bits of the coded bit sequence are repeated so that the length of the rate-matched sequence becomes equal to M. M <N이면, 레이트 매칭된 시퀀스의 길이가 M과 같아지도록, 코딩된 비트 시퀀스의 비트들 중 일부가 펑처링되며, 펑처링된 비트는 전송에서 제외된다.

[0093] That is, in a wireless communication system, the transmitting end encodes data to be transmitted using channel coding having a specific code rate, and then adjusts the code rate of the data to be transmitted through a rate matching process consisting of puncturing and repetition.

[0094] There are various types of error-correcting codes, but the optimal performance is determined by the information block sizes. While many coding schemes are available that offer high capacity information performance at large information block lengths, most of them do not consistently perform well across a wide range of information block lengths and code rates. However, turbo codes, low-density parity check (LDPC) codes, and polar codes have shown promising BLER performance across a wide range of coding rates and code lengths. With the increasing demands for diverse use cases such as enhanced mobile broadband (eMBB), massive IoT, and URLLC, there is a need for coding schemes that offer stronger channel coding efficiency than turbo codes. Furthermore, there is a growing need for increased capacity, i.e., an increase in the maximum number of subscribers that a channel can currently accommodate. Among various error correction codes, polar codes are codes that provide a new framework to solve the problems of existing channel codes. They were invented by Arikan of Bikent University (Reference: E. Arikan, "Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels," in IEEE Transactions on Information Theory, vol. 55, no. 7, pp. 3051-3073, July 2009). Polar codes are the first mathematically proven capacity-achieving codes with low encoding and decoding complexity. Polar codes outperform turbo codes at large information block lengths without any error flow. Hereinafter, channel coding using polar codes is referred to as polar coding.

[0095] Polar codes are known as codes that can achieve channel capacity on a given binary discrete memoryless channel. This can only be achieved when the information block size is sufficiently large. In other words, polar codes are codes that can achieve channel capacity by increasing the code size N infinitely. Polar codes have low encoding and decoding complexity and can be successfully decoded. Polar codes are a type of linear block error-correcting code, and recursive multiple concatenation is the basic building block for polar codes and the basis for code construction. The physical transformation of a channel, which converts physical channels into virtual channels, occurs based on recursive multiple concatenation. When multiple channels are multiplied and accumulated, most of the channels become either better or worse. The idea behind polar codes is to utilize good channels. For example, data is transmitted at rate 1 through good channels and at rate 0 through bad channels. That is, through channel polarization, channels move from a normal state to a polarized state.

[0096] Figure 6 is an example of a block diagram for a polar encoder.

[0097] Figure 6(a) illustrates the base module of a polar code, and in particular, it is a diagram illustrating the first-level channel combining for polar coding. In Figure 6(a), W2 represents the entire equivalent channel obtained by combining two binary discrete memoryless channels (B-DMC), W, . Here, u1 and u2 represent binary input source bits, and y1 and y2 represent output coded bits. Channel combining is the process of concatenating B-DMC channels in parallel.

[0098] Figure 6(b) shows the basic matrix F for the basic module, and the binary input source bits u1, u2 to the basic matrix F and the corresponding output x1, x2 have the following relationship.

[0099]

[0100] Channel W2 can achieve a symmetric capacity I(W), which is the highest rate. In B-DMC W, the symmetric capacity is an important parameter, which is used to measure the rate, and is the highest rate at which reliable communication can occur over the channel W. B-DMC can be defined as follows.

[0101]

[0102] It is possible to synthesize or create a second set of N binary input channels from N independent copies of a given B-DMCW, said channels having properties {W N (i) : 1 <= i <= N}. As N increases, some of the channels tend to have capacities close to 1, while the rest tend to have capacities close to 0. This is called channel polarization. In other words, channel polarization uses N independent copies of a given B-DMCW to create a second set of N channels {W N (i) : is a process that generates {1 <= i <= N}, and the channel polarization effect increases as N increases, all symmetric capacity terms {I(W N (i))} tends to be either 0 or 1 except for the vanishing fraction of these indices i. In other words, the idea behind channel polarization in polar codes is to transform N copies (i.e., N transmissions) of a channel with symmetric capacity I(W) (e.g., an additive white Gaussian noise channel) into extreme channels with capacities close to 1 or 0. Among the N channels, the I(W) fraction will be perfect channels and the 1-I(W) fraction will be completely noise channels. Then, information bits are sent only through good channels, and inputs to other channels are frozen to 1 or 0. The amount of channel polarization increases with the block length. Channel polarization consists of two phases: the channel combining phase and the channel splitting phase.

[0103] Figure 7 illustrates the concept of channel combining and channel splitting for channel polarization. As illustrated in Figure 7, N copies of the original channel W are appropriately combined to create a vector channel W. vec After creating and splitting into new polarized channels, for sufficiently large N, the new polarized channels are each divided into channel capacities C(W)=1 and C(W)=0. In this case, since bits passing through a channel with channel capacity C(W)=1 can be transmitted without error, it is better to transmit information bits through a channel with channel capacity C(W)=1, and since bits passing through a channel with channel capacity C(W)=0 cannot transmit information, it is better to transmit frozen bits, which are meaningless bits.

[0104] Referring to Fig. 7(a), copies of the given B-DMCW are combined recursively to obtain W N : X N →Y NVector channel W given by vec This can be printed. Here, N=2 n , and n is an integer greater than or equal to 0. Recursion always starts at level 0, where W1 = W. n = 1 means the first level of regression, where two independent copies of W1 are combined together. Combining these two copies yields a channel W2: X2 → Y2. The transition probability of this new channel W2 can be expressed by the following equation.

[0105]

[0106] Once the above channel W2 is obtained, a single copy of channel W4 can be obtained by combining two copies of W2. This regression can be expressed by W4: X4→Y4 with the following transition probability.

[0107]

[0108] In Fig. 7(b) G N is a generator matrix of size N. G in Fig. 7(b) N Input to u N 1 and output x N The relationship of 1 is x N 1=u N 1G N can be expressed as . Here x N 1= {x1, ..., x N},u N 1= {u1, ..., u N}. When combining N B-DMCs, each B-DMC can be expressed in a recursive form. That is, G N can be expressed by the following mathematical formula.

[0109]

[0110] Here, ⓧ is the Kronecker product, and N=2 n , F for all n>=1 ⓧn =FⓧF ⓧ(n-1)And, F ⓧ0 = 1.B N is a permutation matrix known as bit-reversal, and B N =R N (I2ⓧB N / 2 ) can be computed recursively. I2 is a 2-dimensional identity matrix, and this recursion is initialized as B2 = I2. R N is a bit-reversal interleaver, with input s N 1= {s1, ..., s N} output x N 1= {s1, s3,..., s N-1 , s2, ..., s N} is used to map. For example, G2 corresponds to the basic matrix F shown in Fig. 6(b). G4 can be expressed as the following matrix.

[0111]

[0112] The bit-reversal interleaver may not be included in the transmission. If the bit-reversal interleaver is not considered, G N = (G2) ⓧn (Here, N=2 n ) can be expressed as (G2) ⓧn is the n-th Kronecker power of matrix G2, where G2 is the same as the elementary matrix F shown in Fig. 6(b).

[0113] The relationship of mathematical expression 5 is illustrated in Fig. 8.

[0114] Figure 8 illustrates N-th level channel combining for polar codes.

[0115] The process of combining N B-DMCWs and then defining an equivalent channel for a specific input is called channel splitting. Channel splitting can be expressed as a channel transition probability, as shown in the following mathematical equation.

[0116]

[0117] Channel polarization has the following characteristics:

[0118] > Conservation: C(W - ) + C(W + ) = 2C(W),

[0119] > Extremization: C(W - ) <= C(W) <= C(W + ).

[0120] After channel combining and channel splitting, the following theorem can be obtained.

[0121] * Theorem: For any B-DMCW, channels {W N (i)} is polarized in the following sense: for any fixed δ∈{0,1}, as N goes to infinity through powers of 2, I(W N (i) )∈(1-δ,1], the fraction of indices i∈{1,...,N} goes to I(W), and I(W N (i) )∈[0,δ) goes to 1-I(W). Therefore, if N→∞, the channels are either completely noisy or are noise-freely polarized, and these channels are known exactly at the transmitter. Therefore, we can fix the bad channels and transmit the unmodulated bits on the good channels.

[0122] That is, when the size N of the polar code becomes infinite, the channel becomes either noisy or noiseless for a specific input bit. This means that the capacity of the equivalent channel for a specific input bit is distinguished as 0 or I(W).

[0123] The input of a polar encoder is divided into bit channels, to which information data is mapped, and bit channels, to which it is not. As previously explained, according to polar code theory, as the number of polar codewords approaches infinity, the input bit channels can be divided into noise-free and noise channels. Therefore, channel capacity can be achieved by assigning information to noise-free bit channels. However, in practice, it is impossible to construct infinitely long codewords. Therefore, the reliability of the input bit channels is calculated and data bits are assigned in that order. In this specification, the bit channels to which data bits are assigned are referred to as "good bit channels." A good bit channel can be considered the input bit channel to which data bits are mapped. The bit channels to which data is not mapped are referred to as "frozen bit channels," and encoding is performed by inputting a known value (e.g., 0) into the frozen bit channels. Any value known to the transmitter and receiver can be mapped to the frozen bit channels. Information about the good bit channels can be utilized when performing puncturing or repetition. For example, codeword bit (i.e., output bit) positions corresponding to input bit positions that are not allocated to information bits may be punctured.

[0124] The decoding method of polar codes is the successive cancellation (SC) decoding method. The SC decoding method calculates the likelihood ratio (LLR) for the input bits by obtaining the channel transition probability. At this time, the channel transition probability can be calculated recursively by taking advantage of the recursive nature of the channel combining and channel splitting processes. Therefore, the final LLR value can also be calculated recursively. First, the input bit u i Channel transition probability W for N (i) (y1 N ,u1 i-1 |u1) can be obtained as follows. u1 i is separated into odd index and even index, u 1,o i , u 1,e i It can be expressed as follows. The channel transition probability can be expressed as the following mathematical formulas.

[0125]

[0126]

[0127] The polar decoder retrieves information, and uses the known values ​​(e.g., received bits, frozen bits, etc.) of the polar code. N 1's estimate u^ N Generates 1. LLR is defined as follows.

[0128]

[0129] LLR can be calculated recursively as follows:

[0130]

[0131] The recursive calculation of LLRs is LLR L (1) 1(yi ) = W(y i |0) / W(y i |1) is traced back to code length 1. L (1) 1(y i ) is soft information observed from the channel.

[0132] The complexity of the polar encoder and SC decoder depends on the length N of the polar code, and is known to have a complexity of O(NlogN). Assuming K input bits in a polar code of length N, the coding rate becomes N / K. The generator matrix of the polar encoder with a data payload size N is G N If so, the encoded bit is x N 1=u N 1G N It can be expressed as, u N K bits in 1 correspond to payload bits and G corresponds to the payload bits. N Let the row index be i, and the remaining NK bits correspond to G N Let the row index of F be . The minimum distance of such polar code is d min (C) = min i∈I 2 wt(i) can be given as, where wt(i) is the number of ones in the binary expansion of i, and i=0,1,...,N-1.

[0133] SC List (SCL) decoding is an extension of the basic SC decoder. In this type of decoder, L decoding paths are considered simultaneously at each stage of decoding, where L is an integer. In other words, for polar codes, the List-L decoding algorithm traces L paths simultaneously during the decoding process.

[0134] Figure 9 illustrates the evolution of decoding paths during List-L decoding. For convenience of explanation, we assume that the number of bits to be determined is n and that not all bits are frozen. If the list size L = 4, each level has at most 4 nodes with paths that continue downward. Discontinuous paths are indicated by dotted lines in Figure 9. Referring to Figure 9, the evolution of decoding paths during List-L decoding is explained as follows. i) List-L decoding begins, and the first unfrozen bit can be either 0 or 1. ii) List-L decoding continues. The second unfrozen bits can be either 0 or 1. Since the number of paths is not more than L = 4, there is no need to prune yet. iii) Considering all options for the first bit (i.e., the bits of the first level), the second bit (i.e., the bits of the second level) and the third bit (i.e., the bits of the third level) results in 8 decoding paths, which is too many since L=4. iv) Pruning the 8 decoding paths into L=4 promising paths. v) Continue the 4 active paths by considering the 2 options for the fourth unfrozen bit. In this case, the number of paths doubles to 8, which is too many since L=4. vi) Again, pruning into L=4 best paths. In the example of Fig. 9, four candidate codewords 0100, 0110, 0111 and 1111 are obtained, and one of them is determined as the codeword most similar to the original codeword. As in a general decoding process, for example, during a pruning process or a process of determining a final codeword, the path with the largest sum of the absolute values ​​of the LLRs can be selected as the survival path.If a CRC is present, a survival path may be selected through the CRC.

[0135] Meanwhile, CRC-aided SCL decoding is SCL decoding using CRC, which improves the performance of polar codes. CRC is the most widely used technique for error detection and error correction in the fields of information theory and coding. For example, if the input block to an error-correcting encoder is K bits, the length of the information bits is k, and the length of the CRC sequence is m bits, then K = k + m. The CRC bits are part of the source bits for the error-correcting code, and if the size of the channel code used for encoding is N, the code rate R is defined as R = K / N. CRC-aided SCL decoding aims to detect error-free paths by checking a cyclic redundancy check (CRC) code for each path at a receiver. The SCL decoder outputs candidate sequences to a CRC detector, which feeds back the check result to assist in codeword determination.

[0136] SCL decoding, or CRC-assisted SCL decoding, is more complex than the SC algorithm but offers superior decoding performance. For more details on the List-L decoding algorithm for polar codes, see I. Tal and A. Vardy, "List decoding of polar codes," in Proc. IEEE Int. Symp. Inf. Theory, pp. 1-5, July 2011.

[0137] Figure 10 is a diagram illustrating the concept of selecting the location(s) to which information bit(s) are to be allocated in a polar code.

[0138] In the example of Fig. 10, it is assumed that the size of the mother code is N=8, that is, the size of the polar code is N=8, and the code rate is 1 / 2.

[0139] C(W) in Fig. 10i ) is channel W i As the capacity of the polar code, it corresponds to the reliability of the channels that the input bits of the polar code will experience. If the channel capacities corresponding to the input bit positions of the polar code are as shown in FIG. 10, the reliability of the input bit positions can be ranked as shown in FIG. 10. In this case, in order to transmit data at a code rate of 1 / 2, the transmitting device allocates the four bits that make up the data to four input bit positions with high channel capacities among the eight input bit positions of the polar code (i.e., the input bit positions indicated as u4, u6, u7, and u8 among the input bit positions u1 to u8 in FIG. 10), and freezes the remaining input bit positions. The generator matrix G8 corresponding to the polar code of FIG. 10 is as follows. The generator matrix G8 is (G2) ⓧn can be obtained based on .

[0140]

[0141] The input bit positions indicated as u1 to u8 in Fig. 10 correspond one-to-one to the rows from the most significant row to the least significant row of G8. Referring to Fig. 10, it can be seen that the input bit corresponding to u8 affects all output coded bits. On the other hand, it can be seen that the input bit corresponding to u1 affects only y1 among the output coded bits. Referring to Equation 12, when the binary input source bits u1 to u8 are multiplied by G8, the row that causes the corresponding input bit to appear in all output bits is the least significant row [1, 1, 1, 1, 1, 1, 1, 1], which is a row of G8 in which all elements are 1. On the other hand, a row that causes the corresponding binary-input source bit to appear in only one output bit is a row of G8 in which one element is 1, i.e., a row weight is 1, [1, 0, 0, 0, 0, 0, 0, 0, 0]. Similarly, a row with a row weight of 2 can be said to reflect the input bit corresponding to the row in two output bits. Referring to FIG. 10 and mathematical expression 12, u1 to u8 correspond one-to-one to the rows of G8, and bit indices can be assigned to the input positions of u1 to u8, i.e., the rows of G8, to distinguish the input positions.

[0142] In polar code, G N It can be assumed that for the N input bits of the row, bit indices are sequentially assigned from bit index 0 to N-1, starting from the top row with the smallest row weight. For example, referring to Fig. 10, bit index 0 is assigned to the input position of u1, i.e., the first row of G8, and bit index 7 is assigned to the input position of u8, i.e., the last row of G8. However, since the bit indices are used to indicate the input positions of the polar code, they can be assigned differently. For example, bit indices 0 to N-1 can be assigned, starting from the bottom row with the largest row weight.

[0143] For the output bit index, as illustrated in Fig. 10 and Equation 12, G N It can be assumed that among the columns, the bit indices are assigned from 0 to N-1, or from 1 to N, from the first column with the largest column weight to the last column with the smallest column weight.

[0144] In polar codes, setting information bits and frozen bits is one of the most important factors in the configuration and performance of the polar code. In other words, determining the rank of input bit positions can be said to be an important factor in the performance and configuration of the polar code. For polar codes, bit indices can distinguish input or output positions of the polar code. For polar codes, a sequence obtained by listing bit positions in ascending or descending order of reliability is called a bit index sequence or polar sequence. In other words, the bit index sequence indicates the reliability of the input or output bit positions of the polar code in ascending or descending order. A transmitting device inputs information bits to input bits with high reliability based on the input bit index sequence and performs encoding using a polar code, and a receiving device can identify input positions to which information bits are assigned or input positions to which frozen bits are assigned using the same or corresponding input bit index sequence. That is, the receiving device can perform polar decoding using the same or corresponding input bit index sequence as the input bit index sequence used by the transmitting device and the corresponding polar code. For the polar code, the input bit index sequence can be assumed to be predetermined so that information bit(s) can be assigned to input bit position(s) with high reliability. In this specification, the input bit index sequence is also referred to as a polar sequence.

[0145] Figure 11 illustrates puncturing and information bit allocation for a polar code. In Figure 11, F represents a frozen bit, D represents an information bit, and 0 represents a skipping bit.

[0146] Depending on the index or position of the punctured bit among the coded bits, there may be cases where the information bits are changed to frozen bits. For example, if the output coded bits for the mother code with N=8 should be punctured in the order of Y8, Y7, Y6, Y4, Y5, Y3, Y2, Y1, and if the target code rate is 1 / 2, as illustrated in FIG. 9, Y8, Y7, Y6, and Y4 are punctured, and U8, U7, U6, and U4, which are only connected to Y8, Y7, Y6, and Y4, are frozen to 0, and these input bits are not transmitted. The input bits that are changed to frozen bits by puncturing of the coded bits are called skipping bits or shortening bits, and the corresponding input positions are called skipping positions or shortening positions. Shortening is a rate matching method that maintains the size of the input information (i.e., the size of the information block) and inserts known bits into the input bit positions associated with the desired output bit positions. Generator matrix G N Shortening is possible starting from the input corresponding to the column with column weight 1 in the matrix, and after removing the columns and rows with column weight 1, the input corresponding to the column with column weight 1 in the remaining matrix can be shortened next. To prevent all the information bits from being punctured, the information bits that should have been assigned to the information bit positions can be reallocated in order of high confidence within the frozen bit position set.

[0147] For polar codes, decoding is typically performed in the following order:

[0148] > 1. Bit(s) with low reliability are restored first. Although it varies depending on the structure of the decoder, since the smaller the input bit index (hereinafter referred to as the encoder input bit index or bit index) in the encoder, the lower the reliability, so decoding is generally performed sequentially starting from the smaller encoder input bit index.

[0149] > 2. If there is known bit information about the restored bit, the known bit is used together with the restored bit, or step 1 is omitted and the known bit for a specific input bit position is used directly to restore the information bit, which is an unknown bit. The information bit may be a source information bit (e.g., a bit of a transport block) or a CRC bit.

[0150] As explained above, through the process of channel combining and channel splitting, the equivalent channel is divided into a noisy channel and a noise-free channel, and the data payload must be transmitted through the noise-free channel. In other words, the data payload must be transmitted through the noise-free equivalent channel to obtain the desired performance. At this time, the noise-free equivalent channel is the value of the equivalent channel for each input bit. can be determined by obtaining Z(W). Z(W) is called the Battacharyya parameter and can be a value corresponding to an upper bound of the error probability when performing a maximum a posteriori probability (MAP) decision for transmitting binary input 0 or 1. Therefore, the transmitter can obtain the value Z(W) and select equivalent channel(s) in ascending order (e.g., small to large) of the value Z(W) to transmit the data payload. Z(W) can be obtained by the following formula for a binary erasure channel (BEC).

[0151]

[0152] For example, when the size of the code block of the BEC channel is 8 with a binary probability of 0.5, the value of Z(W) is calculated using Equation 11 as follows: Z(W) = {1.00, 0.68, 0.81, 0.12, 0.88, 0.19, 0.32, 0.00}. Therefore, when the size of the data payload is 2, the data payload can be transmitted through the equivalent channel 8 with the value Z(W) = 0.00 and the equivalent channel 4 with the value Z(W) = 0.12.

[0153] As mentioned above, since the reliability is different depending on the input positions in the polar encoder, the transmitter can perform encoding by assigning the data block (i.e., the information block before encoding) to the bit channel(s) in order of reliability according to the size of the data block, and setting all the rest to frozen (e.g., value '0'). For example, if the mother code size of the polar encoder (i.e., the maximum size of the code block that the polar encoder can encode) is N, and the size of the data block input to the polar encoder is K, the bits of the data block are arranged in order of reliability on the K bit channels, and the NK bit channel(s) are set to 0 to perform polar encoding.

[0154] The following shows the polar sequences used in NR systems (refer to the polar sequences defined in 3GPP TS 38.212 Rel-15).

[0155] Polar Sequence

[0156]

[0157]

[0158]

[0159]

[0160] The table above shows the polar sequence Q0 Nmax-1 and its corresponding reliability W(Q i Nmax ), and in the table above, W is W(Q i Nmax ) means, and I is Q i Nmax That is, the polar sequence Q0 Nmax-1 = {Q0 Nmax ,Q1 Nmax ,...,Q Nmax-1 Nmax} is given by the table above, where 0 <=Q i Nmax<= Nmax-1 represents the bit index (i.e., bit channel index) before polar encoding for i=0,1,...,Nmax-1, and Nmax=1024 in 3GPP TS 38.212 Rel-15. The polar sequence Q0 Nmax-1 is the ascending order of reliability W(Q0 Nmax ) <W(Q1 Nmax )<... <W(Q Nmax-1 Nmax ), and W(Q i Nmax ) is the bit index Q i Nmax Indicates the reliability of the bit index Q. For example, referring to the table above, the bit index Q i Nmax =4 reliability W(Q i Nmax )=3 is bit index Q i Nmax =3 reliability W(Q i Nmax )=7. In other words, the table above can be said to be a list of bit indices 0 to 1023 representing each of the 1024 input positions of the polar code with Nmax=1024 in ascending order of reliability.

[0161] For any information block encoded to N bits, the same polar sequence Q0 N-1 = {Q0 N ,Q1 N ,Q2 N ,...,Q N-1 N} is used. The above polar sequence Q0 N-1 is the reliability W(Q0 N ) <W(Q1 N ) <W(Q2 N )<... <W(Q N-1 N ) are ordered in ascending order of values ​​less than N. i Nmax with, polar sequence Q0 Nmax-1is a subset of . For example, if N=8, the polar sequence Q0 7 Silver polar sequence Q0 Nmax-1 Among the elements of Q i Nmax <8 elements, Q i Nmax <8 elements have reliability W(0) <W(1)<W(2)<W(4)<W(3)<W(5)<W(6)의 오름차순으로 정렬(order)된다.

[0162] For example, Table 3 shows the input bit positions for an information block of size K=10 from a polar sequence with N=512 to a polar code.

[0163]

[0164] Table 3 shows the 10 elements for K=10 among the elements of the polar sequence with N=512, sorted in ascending order of reliability. Referring to the <Polar sequence> table mentioned above, I(=Q) smaller than N=512 i Nmax ) values, the top 10 confidence levels W(Q) i Nmax ) is {479, 495, 503, 505, 506, 507, 508, 509, 510, 511}, and if {479, 495, 503, 505, 506, 507, 508, 509, 510, 511} are sorted in ascending order of their reliability W, a set of bit indices for K=10 in the polar sequence with N=512 as exemplified in Table 3, {505, 506, 479, 508, 495, 503, 507, 509, 510, 511} can be obtained.

[0165] The bit sequence input to the channel coding is c0,c1,c2,c3,...,c K-1 If we denote it as d0,d1,d2,d3,...,d after encoding the above bits N-1 is represented by where K is the number of bits to be encoded, and N=2 n am.

[0166] For any information block encoded to N bits, the same polar sequence Q0 N-1 = {Q0 N ,Q1 N ,Q2 N ,...,Q N-1 N} is used. The above polar sequence Q0 N-1 is the reliability W(Q0 N ) <W(Q1 N ) <W(Q2 N )<... <W(Q N-1 N ) are ordered in ascending order of values ​​less than N. i Nmax with, polar sequence Q0 Nmax-1 is a subset of .

[0167] Input to polar encoding u = [u0u1u2... u N-1 ], then in some implementations, the output after encoding is d=[d0d1d2d3... d N-1 ] is d=uG N is obtained by, and the encoding can be performed in GF(2).

[0168] The list successive cancellation decoder used in conventional polar code decoding performs alignment operations for each bit, resulting in high implementation complexity and significant delay. To address this, a permutation decoding method has been proposed, which shuffles the order of received signals before decoding.

[0169] Length N=2 nIf the vector π(c) created by rearranging the codeword c of the code C with the permutation π belongs to the original code C, the permutation is called an automorphism. A permutation decoder that generates candidate vectors that permute the received signal using multiple automorphisms and decodes them in parallel can be fully parallelized unlike an SCL decoder and does not require a sorter, which can drastically improve implementation complexity and delay time. In this case, the received signal is σ 2 It is assumed that the signal is transmitted over an additive white Gaussian noise (AWGN) channel with a variance of .

[0170] In order to apply permutation decoding, it is important to find an automorphism, which is a permutation that can be a codeword even if the order of codes is shuffled. In the case of polar codes, for example, an automorphism in the form of an affine transformation can be found depending on the selection of the information set. Polar codes include an automorphism in the form of a block lower triangular affine (BLTA) transformation. The BLTA transformation has different block structures s = (s0,s1,...,s) depending on the selection of the information set. t-1 ) is defined as, and the BLTA transformation process is a binary vector z=(z0,z1,...,z) of the index i of the bit in each codeword. n-1 ) undergoes the following transformation defined for it.

[0171]

[0172] Here each B i,i is s i *s i is an invertible matrix. The BLTA transformation is called the lower triangular affine transformation (s=(1,1,...,1)) and the general affine transformation (s=(n)) depending on the structure of s.

[0173] Some automorphisms for polar codes produce identical successive erasure decoding results during permutation decoding, and are called successive erasure-invariant automorphisms. When using successive erasure-variant automorphisms for permutation decoding of polar codes, each decoding path provides a separate estimate of the transmitted message, which can be used to provide information about the transmitted message.

[0174] Figure 12 is an example of a permutation decoder. In Figure 12, L is the channel output y converted into the log likelihood ratio (LLR) form. For an AWGN channel, L can have the following relationship with the channel output y: L = 2y / σ 2 In, where σ 2 This means a Gaussian distribution.

[0175] The input to the message vector, i.e., the polar encoding block of size N, can be divided into NK frozen bits and K information bits. Since the structure of the polar code and the rate matching structure for the codeword are known to the transmitter and the receiver, the receiver can obtain a channel bit sequence y of length N from the bit sequence received through the physical channel, and can convert the channel bit sequence y into LLR form.

[0176] The successive cancellation (SC) or list-SC decoder of polar codes (corresponding to the SC(L) block in Fig. 12) calculates the log likelihood ratio (LLR) of the channels L0, L1,..., L N-1 LLR L of the message from (0) ,L (1) ,..., L (N-1)are calculated sequentially. At this time, a polarization phenomenon occurs in the distribution of message LLR. As the length N of the code increases, some message LLRs have reliability close to 0, and some LLRs have reliability close to ∞. At this time, a message with reliability of 0 is set to a value shared by the receiver and the transmitter, and communication can be performed by including the actual message in a message with infinite reliability. The decoding process uses the LLR value of the message (i.e., codeword bit) based on the channel LLR within the graph structure of the polar code to determine the bit values ​​of the polar code. In other words, at this time, since the bit value corresponding to the frozen bit among the input bits of the polar code is a value previously shared / known between the transmitter and the receiver, the corresponding channel LLR value is set to infinity, so that polar decoding can be performed. In the decoding process of the polar code, the message vector transmitted by the transmitter is estimated based on the output message LLR information. For example, the LLR value L (i) If >0, the i-th message bit is determined to be “0”.

[0177] Referring to FIG. 12, in some implementations, a permutation decoder performs permutation decoding by generating P decoding paths, applying different permutations to the P decoding paths, decoding the received signal, and selecting the codeword that is closest to the received signal. Each decoding path outputs an individual estimate of the transmitted message, and the different estimates from all decoding paths provide a diversity gain for the transmitted message. In other words, permutation decoding estimates the transmitted codeword independently for each decoding path i and generates an estimate value , so that it can provide diversity gain in the estimation of the transmitted codeword.

[0178] Permutation decoding outputs a decoding failure without further attempts when decoding fails for any decoding path.

[0179] Conventional permutation decoders perform multiple successive erasure decoding passes, each requiring multiple successive erasure decoding attempts. This has the disadvantage of increasing decoding complexity relative to decoding performance.

[0180] To address the problems of conventional permutation decoding, a decoder or decoding process according to some implementations of this specification is described that does not complete decoding for paths judged to have low reliability, and completes decoding only for decoding paths deemed to have higher reliability. According to some implementations of this specification, the decoding complexity can be reduced compared to conventional permutation decoding while achieving performance that is nearly equivalent to that of conventional permutation decoding that decodes all paths to the end.

[0181] A decoding method or decoder according to some implementations of this specification, during a parallel decoding process for decoding paths, determines the reliability of each decoding path based on the magnitude relationship between the minimum log likelihood ratio (LLR) value of each decoding path and a predefined boundary value during decoding.

[0182] Since the minimum LLR value of each decoding path is determined according to the signal-to-noise ratio (SNR) value of the channel, in some implementations of this specification, two boundary values ​​(i.e., threshold values) τ1 and τ2 that determine the reliability of the decoding path can be set / defined to apply to various channels. Using these boundary values, the decoding method or decoder according to some implementations of this specification can not continue decoding for paths that are determined to have low reliability, and can continue decoding to the end only for decoding paths that are determined to have higher reliability. In this way, for path(s) where decoding is performed to the end, the estimated value(s) are obtained as illustrated in FIG. 12, and among the obtained estimated value(s), the estimated value that is closest to the received signal y can be selected as a codeword and output as the overall decoding result. In some implementations, the threshold values ​​τ1 and τ2 may be determined through a trial and error method by trying random values ​​and selecting the value that yields good performance and low complexity.

[0183] In a permutation decoder, the characteristics of distributed CRC are not maintained due to the application of permutation, and permutation decoding must perform inverse permutation and CRC check after decoding all information bits to which permutation has been applied, so early decoding termination by distributed CRC is impossible. In contrast, according to some implementations of the present specification described below, the distributed cyclic redundancy check (CRC) method disclosed in the 5G NR standard document (interleaving disclosed in section 5.3.1.1 of the 3GPP TS 38.212 Rel-15 document, or n disclosed in section 5.3.1.2) PCUnlike u for >0, it has a comparative advantage over distributed CRC in that it can also be used in permutation decoders.

[0184] A decoder or decoding method according to some implementations of this specification, described below, can determine the reliability of a decoding path by utilizing the minimum LLR value of each decoding path during permutation decoding of a polar code, and can reduce decoding complexity by performing decoding only on paths with high reliability. Hereinafter, a decoding method according to some implementations of this specification is described.

[0185] FIG. 13 illustrates an example of a decoding process according to some implementations of the present specification.

[0186] As a way to reduce decoding complexity, it may be considered to terminate the decoding process for unreliable decoding paths early without completing it.

[0187] Some implementations of this specification may first estimate the reliability of each decoding path by utilizing the minimum LLR value of that decoding path obtained during successive cancellation (SC) decoding, in order to achieve performance nearly identical to that of conventional permutation decoding while reducing complexity.

[0188] The SC decoding performance is determined by the bit with the weakest reliability. Therefore, by utilizing the characteristic that the SC decoding performance is determined by the data bit (also called information bit) with the minimum LLR value, as illustrated in FIG. 13, if a decoder or a decoding method according to some implementations of the present specification exists during the SC decoding process, if a data bit with an LLR value smaller than a predefined boundary value (hereinafter, τ1) exists, the decoding path is determined to have low reliability and the decoding is stopped or terminated.

[0189] The decoding method illustrated in Fig. 13 is particularly effective in channels with low signal-to-noise ratio (SNR) values. This is because, when the channel SNR is low, the minimum LLR value of each decoding path will be low.

[0190] Figure 14 illustrates another example of a decoding process according to some implementations of the present specification.

[0191] The implementations of the present specification described with reference to FIG. 13 are methods for reducing complexity by preemptively identifying paths with a high probability of decoding failure during parallel SC decoding and terminating decoding on those paths. In channels with high SNR values, the minimum LLR value of each decoding path becomes relatively large. Therefore, in the case of channels with high SNR values, the number of paths that are terminated during decoding due to the boundary value τ1 becomes extremely small, and thus the complexity may not be reduced. Taking this into account, as another or additional method for reducing decoding complexity, reducing the number of paths to be decoded may be considered. A decoder or decoding method according to some implementations of the present specification can reduce decoding complexity by preemptively identifying path(s) with a high probability of decoding success and performing decoding to the end only on those decoding path(s).

[0192] In some implementations of this specification, a new boundary value (hereinafter, τ2) that serves as a criterion for determining the reliability of each decoding path and the number L of paths that actually perform decoding to the end ccan be used. One of the main goals of some implementations of this specification is to achieve a performance similar to that obtained by using all decoding paths of a given polar decoder while effectively reducing complexity. To achieve this goal, if the decoding paths are divided based on a fixed threshold value τ2, the number of paths considered reliable increases as the SNR value of the channel to which the decoding method according to some implementations of this specification, as illustrated in Fig. 14, is applied, and thus the effect of the method is minimal. Therefore, some decoders or decoding methods according to some implementations of this specification first sort the minimum LLR values ​​of each (respective) decoding path for decoding paths that are determined to be reliable by the new threshold value τ2, and select the LLR with the largest minimum LLR value. c The final path(s) are selected, and decoding is performed to the end only for those path(s). τ2 and L cBy utilizing , the decoding process can be performed as illustrated in Fig. 14. In order to efficiently reduce the complexity, a new threshold τ2 for judging the reliability of each decoding path is applied to the middle of the SC decoding (e.g., a specific bit(s) of the SC decoding process along the path, and the location is referred to as a test region in this specification, and is the M-th weakest information bit (i.e., the bit index M that is used for the data bit among the bit indices of the polar code and has the highest error probability). In some implementations of this specification, the t bits with the lowest reliability among the K information bits may be selected as the test region so as to effectively screen out low-reliability paths. In some implementations of this specification, the test region includes the bit(s) with the highest error probability, and the size of the test region is described below. M, which represents the test region, is selected so that the data bits with a high probability of having a small LLR value are effectively included by utilizing the probability density function (PDF) of each data bit. The method described with reference to FIG. 14, i.e., τ2 and L c The method of utilizing τ1, as described with reference to FIG. 13, can effectively reduce decoding complexity in channels with high SNR values.

[0193] The method described in Fig. 13 and the method described in Fig. 14 may be applied separately or together.

[0194] Figure 15 shows the changes in the minimum log likelihood ratio (LLR) values ​​of each decoding path in sequential decoding according to the bit indices (hereinafter, data bit indices or information bit indices) where data / information is arranged. In the example of Figure 15, the number of decoding paths P = 4, L c= 2 is assumed. Referring to Fig. 15, τ1 is dominant in the low SNR region and τ2 and L c It can be seen that the decoding complexity is dominant in the high SNR region. As illustrated in Fig. 15, the decoding complexity can be effectively reduced for channels with various SNR values ​​using the method described in Fig. 13 and the method described in Fig. 14.

[0195] Low-complexity permutation SC decoding according to some implementations of this specification performs early termination by comparing the minimum LLR values ​​of test points in the test region with given threshold values ​​τ1 and τ2. The size of the test region (i.e., the number of test points) can be determined based on the reliability of the information bits (i.e., data bits). For example, the test region size can be determined as follows.

[0196] Figures 16 and 17 illustrate a method for determining the size of a test area according to some implementations of the present specification.

[0197] The block error rate (BLER) of a typical permutation SC decoding path can be expressed as follows.

[0198]

[0199] BLER in Fig. 16 and the mathematical formula above ns is the BLER of the non-skipped path, and P e_i is the error probability of the i-th bit among the information bits, and K is the number of information bits (i.e., data bits). In the example of Fig. 16, K = 4, and the set of most reliable bit indices among the bit indices 1 to 8 to the polar encoder is {4, 6, 7, 8}.

[0200] Referring to Figure 17, the test area I that constitutes t test points in the above mathematical formulaT = {1, 2, ..., t}, the BLER of a path where decoding terminates early according to some implementations of this specification can be expressed as follows.

[0201]

[0202] Here, BLER l is the BLER of path l whose decoding is terminated by τ1, and P e_i (τ1) is the error probability of the i-th bit when the absolute value LLR value of the i-th bit is less than τ1.

[0203] In some implementations of this specification, the test area may be determined such that the following two conditions are met:

[0204] 1) The test area includes the bit with the highest error probability; and

[0205] 2) The size of the test area must be guaranteed to satisfy BLER. ns Wow BLER l It must be ensured that they are approximately equal.

[0206] That is, the test area must satisfy the above two conditions, so that the test area contains t bits with the highest error probability.

[0207] Two metrics can be considered to indicate the degree of complexity reduction achieved by some implementations of this specification. The first is a metric expressed in terms of decoding paths, which represents the ratio of the number of paths whose decoding is terminated in the middle by two boundary values ​​τ1 and τ2 according to some implementations of this specification to the total number of decoding paths of the polar decoder of Fig. 12, and can be expressed as follows.

[0208]

[0209] Another measure is the measure expressed in terms of data bits for which decoding is performed, representing the ratio of the number of data bits that need to be decoded in the existing polar decoder of Fig. 12 to the number of data bits that do not need to be decoded due to decoding being terminated midway. In the equation below expressing this measure, K represents the total number of data bits contained in the codeword.

[0210]

[0211] In a polar code, the reliability of each information bit can be determined by the code structure. The (N, K) code structure depends on the size N of the polar code and the number K of information bits input to the polar encoding block, and the K bit indices where K information bits are arranged among the N bit indices of the polar code (i.e., bit positions of the polar code) can be determined according to the reliability of the bit indices.

[0212] Figures 18 to 23 illustrate bit error probabilities for code structures. In particular, Figures 18 to 20 illustrate bit error probabilities for a channel using (N, K) = (512, 251) polar codes and having a channel SNR of 2 dB, and Figures 21 to 23 illustrate bit error probabilities for a channel using (N, K) = (1024, 517) polar codes and having a channel SNR of 3 dB. Referring to Figures 18 to 23, it can be seen that the error probabilities of early information bits tend to be greater than those of later information bits due to the polar code characteristics. Therefore, τ1 can reduce the complexity of SC decoding even if it is applied only to early information bits. Since SC decoding of polar codes is dominantly affected by the information bit with the highest error probability, the reliability of SC decoding can be determined through the information bit with the highest reliability.

[0213] Figures 24 and 25 illustrate the word error ratio (WER) and complexity performance of decoding methods according to some implementations of the present specification. In particular, Figures 24 and 25 illustrate the WER and complexity performance of decoding methods according to some implementations of the present specification for (N, K) = (1024, 632) polar codes.

[0214] The graphs shown in Fig. 24 show: 1) the WER of the existing permutation decoding method (see "Perm-SC" in Fig. 24), and 2) τ1, τ2, and L according to some implementations of this specification. c WER of the decoding method applied (see "Proposed" in Fig. 24). In Fig. 24, P=32, τ1=0.2, τ1=5.5, L c =4 was used. As shown in Fig. 24, it can be confirmed that there is little performance loss compared to conventional permutation decoding even when using some implementations of this specification that terminate early for some decoding paths and / or decode only the decoding path(s) with the largest minimum LLR value(s).

[0215] Meanwhile, Fig. 25 compares the complexity performance through the two measures presented above (see Equations 17 and 18). Referring to Fig. 25, when the SNR value is 5, the proportion of skipped paths is approximately 80%, so the proportion of paths that have actually completed decoding among the total permutation paths is approximately 20%. The graph of Fig. 25 shows that, in terms of decoding paths and data bits, even if only up to 20% of the total decoding paths are utilized, the same performance can be achieved as the conventional permutation decoding that performs decoding on all decoding paths.

[0216] The performance evaluations illustrated in FIGS. 24 and 25 demonstrate that decoding methods according to some implementations of the present specification reduce the complexity of existing permutation decoding methods under various channels.

[0217] According to some implementations of this specification, decoding may be terminated early for path(s) where SC decoding is likely to fail. In addition, according to some implementations of this specification, the decoder may terminate the upper-L c Since sufficient decoding reliability can be achieved with only a few of the most reliable paths, the number of decoding paths can be reduced, thereby increasing decoding speed and reducing decoding complexity. Furthermore, unlike distributed CRCs, which cannot be used for permutation decoding, some implementations of this specification allow early decoding termination for permutation decoding.

[0218] Figure 26 illustrates different decoding flows for some implementations of this specification.

[0219] A communications device or decoder may perform operations according to some implementations of the present disclosure in connection with channel decoding. The communications device or decoder may include at least one transceiver; at least one processor; and at least one computer memory operably connected to the at least one processor and storing instructions that, when executed, cause the at least one processor to perform operations according to some implementations of the present disclosure. A processing device for the communications device or decoder may include at least one processor; and at least one computer memory operably connected to the at least one processor and storing instructions that, when executed, cause the at least one processor to perform operations according to some implementations of the present disclosure. A computer-readable (non-volatile) storage medium may store at least one computer program comprising instructions that, when executed by at least one processor, cause the at least one processor to perform operations according to some implementations of the present disclosure. A computer program or computer program product may be recorded on at least one computer-readable (non-volatile) storage medium and may contain instructions that, when executed, cause (at least one processor) to perform operations according to some implementations of the present specification.In the above communication device, the decoder, the processing device, the computer-readable (non-volatile) storage medium, and / or the computer program product, the operations may include: receiving a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; obtaining a first bit sequence of length N from the bit sequence y (S2601); applying P different permutations to the first bit sequence to generate P second bit sequences (S2603), where P is an integer greater than 1; performing successive erasure decoding based on the P second bit sequences (S2605); and determining a codeword based on the successive erasure decoding (S2607). The successive erasure decoding (S2607) may include: selecting, from among the P second bit sequences, L. having top minimum LLR values ​​greater than a predetermined second threshold τ2. c It may include completing decoding only for each of the second bit sequences, where L c is a positive integer less than P.

[0220] In some implementations, the successive erasure decoding (S2607) is performed if: i) the minimum LLR value among the LLR values ​​of the least reliable t information bits is not greater than τ2, or ii) the L c It may include terminating before completing decoding for a second bit sequence that does not belong to the second bit sequences.

[0221] In some implementations, the successive erasure decoding (S2607) may include: terminating decoding for a second bit sequence having an information bit having an LLR value less than a predefined first threshold τ1 among the P second bit sequences at the information bit having the LLR value less than τ1.

[0222] In some implementations, the successive erasure decoding (S2607) may include: comparing the LLR values ​​of the least reliable t information bits in each of the P second bit sequences with τ1; and terminating decoding for the second bit sequence at an information bit among the least reliable t information bits having an LLR value less than τ1.

[0223] In some implementations, t is It can be a positive integer satisfying , And, and I T = {1, 2, ..., t}, K is the number of information bits, and P e_i is the error probability of the i-th bit among the above K information bits.

[0224] In some implementations, the encoded bit sequence may be obtained based on the polar code having K information bits and size N.

[0225] In some implementations, the method may include determining an information bit sequence of length K based on a polar sequence of length N that sorts the N bit indices of the codeword and the polar code of length N by reliability.

[0226] In some implementations, the successive erasure decoding (S2607) comprises: c L based on the second bit sequences of the dog c Output the third bit sequences; and the L c It may include outputting, as the codeword, a bit sequence that minimizes the distance between the bit sequence y and the third bit sequence among the third bit sequences.

[0227] In some implementations of the present specification, the communication device or decoder may establish a radio resource control (RRC) connection for communication with another communication device (e.g., UE or BS), and receive a signal related to the first bit sequence of length N from the communication device. For example, based on the signal transmission / reception process described in FIGS. 27 and 28, a signal including part or all of a bit sequence encoded by a polar code having a length of N can be received from the other communication device through a physical channel (e.g., a physical uplink control channel (PUCCH), a physical uplink shared channel (PUSCH), a physical downlink control channel (PDCCH), a physical downlink shared channel (PDSCH), a physical broadcast channel (PBCH), a physical sidelink control channel (PSCCH), a physical sidelink shared channel (PSSCH), or a physical sidelink broadcast channel (PSBCH).The above physical channel can carry a rate-matched codeword obtained by rate-matching a codeword (e.g., a codeword of length N) of uplink control information (UCI), uplink shared channel (UL-SCH) data, a master information block (MIB) which is part of minimum system information, downlink control information (DCI), downlink shared channel (DL-SCH) data, or sidelink shared channel (SL-SCH) data. A communication device transmitting the rate-matched codeword or a corresponding encoder can perform rate matching on the codeword based on a radio resource allocated for transmission of the codeword and a target code rate for the corresponding physical channel, and transmit the rate-matched codeword as a transmission sequence to a counterpart communication device. A communication device or decoder receiving the rate-matched codeword can obtain a first bit sequence of length N from a received signal.

[0228] Figure 27 illustrates physical channels used in a 3GPP-based communication system, which is an example of a wireless communication system, and a signal transmission / reception process using the channels.

[0229] When a UE is powered on again after being powered off or has been disconnected from a wireless communication system, it first searches for a suitable cell to camp on (search cell) and performs an initial cell search process, such as synchronizing with the cell or the BS of the cell (S11). During the initial cell search process, the UE receives a synchronization signal block (SSB) (also called an SSB / PBCH block) from the BS. The SSB includes a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH). The UE synchronizes with the BS based on the PSS / SSS and obtains information such as a cell identity (ID). In addition, the UE can obtain broadcast information within the cell based on the PBCH. Meanwhile, the UE can check the downlink channel status by receiving a downlink reference signal (DL RS) during the initial cell search process.

[0230] A UE that has completed initial cell search can camp on the cell. After camping on the cell, the UE monitors the PDCCH on the cell and receives the PDSCH based on the downlink control information (DCI) carried by the PDCCH to obtain more specific system information (S12).

[0231] Thereafter, the UE may perform a random access procedure to complete access to the BS (S13 to S16). For example, in the random access procedure, the UE may transmit a preamble through a physical random access channel (PRACH) (S13) and receive a random access response (RAR) to the preamble through a PDCCH and a corresponding PDSCH (S14). If reception of the RAR for the UE fails, the UE may retry transmitting the preamble. In the case of contention-based random access, a contention resolution procedure (S16) may be performed, including transmission of a PUSCH based on UL resource allocation included in the RAR (S15) and reception of a PDCCH and a corresponding PDSCH.

[0232] The UE, which has performed the procedure described above, can then perform reception of PDCCH / PDSCH (S17) and transmission of PUSCH / PUCCH (S19) as a general uplink / downlink signal transmission process. The control information that the UE transmits to the BS is collectively referred to as uplink control information (UCI). UCI includes HARQ ACK / NACK (Hybrid Automatic Repeat and reQuest Acknowledgement / Negative-ACK) (also referred to as HARQ-ACK), scheduling request (SR), channel state information (CSI), etc. CSI may include a channel quality indicator (CQI), a precoding matrix indicator (PMI), and / or a rank indicator. UCI is generally transmitted through PUCCH, but may be transmitted through PUSCH when control information and traffic data must be transmitted simultaneously. Additionally, based on a request / instruction from the network, the UE can transmit UCI aperiodically via PUSCH.

[0233] Figure 28 illustrates a random access process that may be applied to implementation(s) of the present specification. In particular, Figure 28(a) illustrates a four-step random access process, and Figure 28(b) illustrates a two-step random access process.

[0234] The random access procedure can be used for various purposes, including initial access, uplink synchronization adjustment, resource allocation, handover, wireless link reconfiguration after a wireless link failure, and position measurement. The random access procedure is classified into a contention-based procedure and a dedicated (i.e., non-contention-based) procedure. The contention-based random access procedure is commonly used, including initial access, while the dedicated random access procedure is used for handovers, when downlink data arrives in the network, and to reestablish uplink synchronization in the case of position measurement.

[0235] A PRACH preamble configuration to be used may be provided to the UE. Multiple RACH preamble formats (i.e., PRACH preamble formats) are defined by one or more RACH OFDM symbols, and different cyclic prefixes (CPs) (and / or guard occasions). The PRACH preamble configuration for a cell provides the UE with the PRACH preamble formats and RACH occasion(s) available on the cell. A RACH occasion represents the time-frequency resource available for transmission / reception of RA preamble(s). In some scenarios, one RACH occasion (RO) is configured by an RRC message (e.g., SIB2 of the cell) for all possible RA preambles that may be transmitted on the cell. In some other scenarios, SSBs may be selected to be associated with different beams, and the association between SSBs and RACH occasions may be provided to the UE by the BS. SSBs associated with different downlink beams of a cell can be identified by different SSB indices, and different SSB indices can represent different downlink beams. The BS provides an available set of RACH occasions for transmission of an RA preamble and the RACH occasion(s) associated with an SSB via a PRACH configuration including a PRACH preamble configuration. For example, the number of SSBs associated with one RACH occasion can be provided to the UE via a higher layer (e.g., RRC) parameter SSB-perRACH-Occasion. Based on the PRACH configuration for a cell, each of the SSBs transmitted on the cell is associated with one or more RACH occasions. The BS can provide the UE with the number of preambles per SSB via the PRACH configuration. For example, the number of preambles per SSB can be provided by the value of a higher layer parameter cb-preamblePerSSB.The UE may determine the total number of preambles per SSB per RACH epoch based on the values ​​of SSB-perRACH-Occasion and cb-preamblePerSSB. SSB indices may be mapped to RACH epochs in the following order:

[0236] - First, in increasing order of preamble indices within a single RACH period;

[0237] - Second, in increasing order of frequency resource indices for frequency multiplexed RACH periods;

[0238] - Thirdly, in increasing order of time resource indices for time-multiplexed RACH epochs within a RACH slot;

[0239] - Fourth, in increasing order for RACH slots.

[0240] In some scenarios where SSBs are associated with different downlink beams, a UE may detect one or more SSBs on a cell, select an SSB among the detected SSBs (randomly or based on a corresponding reference signal received power (RSRP)), and determine a RACH occasion associated with the selected SSB for the PRACH configuration. The UE may transmit an RACH preamble on the determined RACH occasion. A BS may monitor available RACH occasions on the cell and, based on the RACH occasion in which the RACH preamble is received, may know which SSB the UE transmitting the RA preamble has selected among SSBs of different SSB indices transmitted by the BS on the cell. The BS may determine a downlink beam suitable for the UE based on the SSB selected by the UE.

[0241] During contention-based random access, the UE selects a random access (RA) preamble. In contention-based random access, multiple UEs can simultaneously transmit the same RA preamble, necessitating subsequent contention resolution. In contrast, during dedicated random access, the UE uses an RA preamble uniquely assigned to it by the BS. Therefore, the UE can perform the random access process without conflict with other UEs.

[0242] Referring to Fig. 28(a), the contention-based random access process includes the following four steps. Hereinafter, the messages transmitted in steps 1 through 4 may be referred to as Msg1 through Msg4, respectively.

[0243] - Step 1: The UE transmits an RA preamble via PRACH.

[0244] - Step 2: The UE receives a random access response (RAR) from the BS via PDSCH.

[0245] - Step 3: The UE transmits UL data to the BS via PUSCH based on the RAR. Here, the UL data includes layer 2 and / or layer 3 messages.

[0246] - Step 4: The UE receives a contention resolution message from the BS via PDSCH.

[0247] The UE can receive information about random access from the BS through system information. If random access is required, the UE transmits Msg1 (e.g., preamble) to the BS on the PRACH. The BS can distinguish each random access preamble through the RACH occasion (RO), which is the time / frequency resource on which the random access preamble is transmitted, and the random access preamble index (PI). When the BS receives the random access preamble from the UE, the BS transmits a RAR message to the UE on the PDSCH. To receive a RAR message, the UE monitors a circular redundancy check (CRC) masked L1 / L2 control channel (PDCCH) with a random access (RA) radio network temporary identifier (RNTI) (RA-RNTI), which contains scheduling information for the RAR message, within a preset time window (e.g., ra-ResponseWindow). When scheduling information is received through the PDCCH masked with the RA-RNTI, the UE can receive an RAR message from a PDSCH indicated by the scheduling information. Thereafter, the UE determines whether an RAR for itself is included in the RAR message. Whether an RAR for itself exists can be determined by whether a Random Access preamble ID (RAPID) for a preamble transmitted by the UE exists. The index of the preamble transmitted by the UE and the RAPID may be the same. The RAR includes a corresponding random access preamble index, timing offset information for UL synchronization (e.g., timing advance command (TAC), UL scheduling information for Msg3 transmission (e.g., UL grant), and UE temporary identification information (e.g., temporary-C-RNTI, TC-RNTI).The UE receiving the RAR transmits Msg3 via PUSCH according to the UL scheduling information and timing offset value in the RAR. Msg3 may include the ID of the UE (or the global ID of the UE). Additionally, Msg3 may include information related to an RRC connection request for initial access to the network (e.g., an RRCSetupRequest message). After receiving Msg3, the BS transmits Msg4, which is a contention resolution message, to the UE. If the UE receives the contention resolution message and contention resolution is successful, the TC-RNTI is changed to a C-RNTI. Msg4 may include the ID of the UE and / or information related to RRC connection (e.g., an RRCSetup message). If the information transmitted via Msg3 does not match the information received via Msg4, or if Msg4 is not received for a certain period of time, the UE may consider contention resolution to have failed and retransmit Msg3. A UE that successfully resolves the contention can transition to the RRC_CONNECTED state. For a UE in RRC_CONNECTED state, RRC messages can be exchanged between the UE's RRC layer and the BS's RRC layer. In other words, a UE in RRC_CONNECTED state can refer to a UE for which an RRC connection has been established between the UE and the BS.

[0248] Meanwhile, the dedicated random access process includes the following three steps. Hereinafter, the messages transmitted in steps 0 to 2 may be referred to as Msg0 to Msg2, respectively. The dedicated random access process may be triggered in the UE by the BS using a PDCCH (hereinafter, PDCCH order) for commanding the transmission of an RA preamble.

[0249] - Step 0: BS allocates RA preamble to UE through dedicated signaling.

[0250] - Step 1: The UE transmits an RA preamble via PRACH.

[0251] - Step 2: The UE receives RAR via PDSCH from the BS.

[0252] The operation of steps 1 and 2 of the dedicated random access process may be identical to steps 1 and 2 of the contention-based random access process.

[0253] Future wireless communication systems may require lower latency than existing systems. Furthermore, a four-step random access process may not be desirable, especially for latency-sensitive services such as URLLC. A low-latency random access process may be required in various scenarios of wireless communication systems. When implementing the implementation(s) of this specification in conjunction with a random access process, the implementation(s) of this specification may be implemented in conjunction with the following two-step random access process to reduce the latency of the random access process.

[0254] Referring to Fig. 28(b), the two-step random access process may be composed of two steps: transmission of MsgA from a UE to a BS and transmission of MsgB from the BS to the UE. The MsgA transmission may include transmission of an RA preamble via a PRACH and transmission of an UL payload via a PUSCH. In the MsgA transmission, the PRACH and PUSCH may be transmitted using time division multiplexing (TDM). Alternatively, in the MsgA transmission, the PRACH and PUSCH may be transmitted using frequency division multiplexing (FDM).

[0255] A BS that receives MsgA can transmit MsgB to the UE. MsgB can include an RAR for the UE.

[0256] An RRC connection request related message (e.g., an RRCSetupRequest message) requesting to establish a connection between the RRC layer of the BS and the RRC layer of the UE may be transmitted in the payload of MsgA. In this case, MsgB may be used to transmit RRC connection related information (e.g., an RRCSetup message). Alternatively, the RRC connection request related message (e.g., an RRCSetupRequest message) may be transmitted via a PUSCH transmitted based on a UL grant in MsgB. In this case, the RRC connection related information (e.g., an RRCSetup message) related to the RRC connection request may be transmitted via a PDSCH associated with the PUSCH transmission after the PUSCH transmission based on MsgB.

[0257] A UE that successfully receives MsgB associated with MsgA transmitted by the UE may transition to the RRC_CONNECTED state. For a UE in RRC_CONNECTED state, RRC messages may be exchanged between the RRC layer of the UE and the RRC layer of the BS. In other words, a UE in RRC_CONNECTED state may refer to a UE for which an RRC connection has been established between the UE and the BS.

[0258] A receiving communication device can receive radio frequency (RF) signals at a carrier frequency via at least one antenna. In some implementations, the RF signals can include a signal associated with an encoded bit sequence of length N. For example, the method or operations of the communication device can include: receiving a radio signal from another communication device via a physical channel on a serving cell of the communication device based on the random access procedure; performing frequency downconversion on the received radio signal to obtain an orthogonal frequency division multiplexing (OFDM) baseband signal; and obtaining complex-valued modulation symbols of the physical channel based on the OFDM baseband signal; and obtaining a first bit sequence of length N based on the complex-valued modulation symbols of the physical channel. The first bit sequence of length N can be decoded according to some implementations of the present disclosure.

[0259] As described above, the examples disclosed herein are provided to enable those skilled in the art to implement and practice the present disclosure. While the examples have been described above with reference to the examples of the present disclosure, those skilled in the art will appreciate that various modifications and variations may be made to the examples of the present disclosure. Accordingly, the present disclosure is not intended to be limited to the examples described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0260] Implementations of this specification can be used in wireless communication systems, BSs, UEs, and other equipment.

Claims

1. When a communication device decodes a received signal in a wireless communication system, Receive a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; Obtain a first bit sequence of length N from the above bit sequence y; Generating P second bit sequences by applying P different permutations to the first bit sequence, where P is an integer greater than 1; Performing successive erasure decoding based on the above P second bit sequences; and Including determining a codeword based on the above successive erasure decoding, The above continuous erasure decoding is: Among the above P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values greater than a predetermined second threshold τ2. c Including completing decoding only for each of the second bit sequences, where L c is a positive integer less than P, How to decode.

2. In paragraph 1, The above continuous erasure decoding is: i) the minimum LLR value among the LLR values of the least reliable t information bits is not greater than τ2, or ii) the L c Terminating before completing decoding of a second bit sequence that does not belong to the second bit sequences, How to decode.

3. In paragraph 1, The above continuous erasure decoding is: Including decoding a second bit sequence having an information bit having an LLR value less than a predefined first threshold τ1 among the P second bit sequences, terminating the decoding at the information bit having an LLR value less than τ1. How to decode.

4. In paragraph 3, The above continuous erasure decoding is: Compare the LLR values of the least reliable t information bits with τ1 in each of the P second bit sequences; and terminating decoding for the second bit sequence at an information bit having an LLR value less than τ1 among the least reliable t information bits, How to decode.

5. In paragraph 1, The above encoded bit sequence is obtained based on the polar code having K information bits and size N. How to decode.

6. In paragraph 5, Determining an information bit sequence of length K based on a polar sequence of length N that sorts N bit indices of the codeword and the polar code of length N according to reliability. How to decode.

7. In paragraph 1, The above continuous erasure decoding is: Above L c L based on the second bit sequences of the dog c Output the third bit sequences; and Above L c Including outputting, as the codeword, a bit sequence that minimizes the distance between the bit sequence y and the third bit sequence among the third bit sequences. How to decode.

8. In a wireless communication system, when a communication device decodes a received signal, At least one transceiver; at least one processor; and At least one computer memory operably connected to said at least one processor and storing instructions that, when executed, cause said at least one processor to perform operations, said operations comprising: Receive a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; Obtain a first bit sequence of length N from the above bit sequence y; Generating P second bit sequences by applying P different permutations to the first bit sequence, where P is an integer greater than 1; Performing successive erasure decoding based on the above P second bit sequences; and Including determining a codeword based on the above successive erasure decoding, The above continuous erasure decoding is: Among the above P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values greater than a predetermined second threshold τ2. c Including completing decoding only for each of the second bit sequences, where L c is a positive integer less than P, Communication device.

9. In a processing device in a wireless communication system, at least one processor; and At least one computer memory operably connected to said at least one processor and storing instructions that, when executed, cause said at least one processor to perform operations, said operations comprising: Receive a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; Obtain a first bit sequence of length N from the above bit sequence y; Generating P second bit sequences by applying P different permutations to the first bit sequence, where P is an integer greater than 1; Performing successive erasure decoding based on the above P second bit sequences; and Including determining a codeword based on the above successive erasure decoding, The above continuous erasure decoding is: Among the above P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values greater than a predetermined second threshold τ2. c Including completing decoding only for each of the second bit sequences, where L c is a positive integer less than P, Processing unit.

10. In a computer-readable storage medium, The storage medium stores at least one program code including instructions that, when executed, cause at least one processor to perform operations, the operations comprising: Receive a bit sequence y associated with an encoded bit sequence of length N based on a polar code of size N, where N is an integer greater than 1; Obtain a first bit sequence of length N from the above bit sequence y; Generating P second bit sequences by applying P different permutations to the first bit sequence, where P is an integer greater than 1; Performing successive erasure decoding based on the above P second bit sequences; and Including determining a codeword based on the above successive erasure decoding, The above continuous erasure decoding is: Among the above P second bit sequences, L has the highest minimum log likelihood ratio (LLR) values greater than a predetermined second threshold τ2. c Including completing decoding only for each of the second bit sequences, where L c is a positive integer less than P, Storage medium.

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