Communication method based on modified polarization-adjusted convolutional codes and communication apparatus

Abstract

The present application provides a communication method based on modified polarization-adjusted convolutional (MPAC) codes. According to the method, on the basis of the performance criterion of AUB, from among multiple candidate information length Kc and code length Nc pairs, one information length and code length pair can be determined as parameters of a partial convolutional code for MPAC, wherein the information length and the code length are two values in a first parameter group, so that MPAC coding can be carried out on an information bit sequence to be coded to obtain a first MPAC codeword sequence. Compared with a Polar code and a PAC code, the obtained MPAC code has better performance and lower complexity. Moreover, the first information length and the first code length in the determined first parameter group are sent out, so that the obtained first MPAC codeword sequence is subsequently subjected to MPAC decoding on the basis of the first parameter group, thereby perfecting the MPAC coding and decoding structure.

Description

A communication method and communication device based on improved polarization adjustment convolutional code

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on March 13, 2024, with application number 202410292242.6, and the priority of the Chinese patent application entitled “A communication method and communication device based on improved polarization-adjusted convolutional code”, all contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communication technology, and more particularly, to a communication method and a communication device based on an improved polarization-adjusted convolutional code. Background Art

[0003] As a core technology for ensuring reliable information transmission, channel coding has played a crucial role in the evolution of wireless communication systems. For ultra-reliable low latency communication (uRLLC) scenarios in next-generation communication systems, existing long codes struggle to meet the requirements for low decoding latency and low complexity. Therefore, channel coding with medium to short code lengths is crucial.

[0004] Currently, high-performance short- to medium-length codes include Bose-Chaudhuri-Hocquenghem (BCH) codes, tail-biting convolutional (TBC) codes, cyclic redundancy check (CRC)-Polar concatenated codes, and polarization-adjusted convolutional (PAC) codes. These short- to medium-length codes can effectively approach finite code length rates through specific decoding methods. However, improved decoding performance comes at the cost of increased decoding complexity. For example, successive cancellation list (SCL) decoding of CRC-polar codes can only achieve maximum likelihood (ML) performance when the decoding list is sufficiently large, resulting in high decoding complexity and latency. For another example, PAC codes, assisted by a Fano decoder, can approach finite code length performance, but this comes with the disadvantages of uncontrollable decoding latency and complexity. Therefore, a coding scheme that can achieve a compromise between decoding performance and decoding complexity is sought, which can avoid the two extreme situations of good decoding performance but too high decoding complexity and low decoding complexity but too poor decoding performance.

[0005] In recent years, a scheme for improving PAC (modified PAC, MPAC) codes based on partial convolution and a hybrid decoding strategy has been proposed. The hybrid Fano-successive cancellation (HFSC) decoding of this MPAC code achieves good decoding performance while maintaining low decoding complexity, while limiting decoding complexity. Because MPAC codes are encoded based on partial convolution, the information length and code length used for partial convolution play a significant role in their ML performance. Currently, there is no clear solution for determining the information length and code length used for partial convolution. Therefore, determining these information lengths and code lengths remains an urgent issue. Summary of the Invention

[0006] The present application provides a communication method based on an improved polarization-adjusted convolutional code, which can be used to determine the information length and code length used for partial convolution in MPAC coding, thereby improving the MPAC coding structure.

[0007] In a first aspect, a communication method based on an improved polarization-adjusted convolutional code is provided, the method comprising: obtaining a first sequence to be encoded, the first sequence comprising K information bits, K ≥ 1; determining a first parameter group from a plurality of parameter groups, each parameter group comprising a first value K c and the second value N c , the first value K c is a candidate value of the number of information bits included in the first subsequence that needs to be convolutionally transformed among the K information bits, and the second value N c is a candidate value of the number of bits included in the second sequence obtained after the convolution transformation of the first subsequence, 1≤K c ≤K,N c ≥1, K c ≤N c ; Performing improved polarization adjustment convolutional code MPAC encoding on the first sequence according to the first parameter group to obtain a first MPAC codeword sequence; sending the first MPAC codeword sequence and first indication information, where the first indication information is used to indicate the first parameter group.

[0008] Based on the above scheme, when there is an information bit sequence to be encoded, it is possible to select from multiple candidate information lengths K c Sum code length N cIn the combination, an information length and a code length are determined as parameters for MPAC partial convolutional coding. The information length and code length are two values ​​in the first parameter group, so that MPAC encoding can be performed on the information bit sequence to be encoded to obtain a first MPAC codeword sequence. Furthermore, the determined first parameter group can be transmitted so that the obtained first MPAC codeword sequence can subsequently be MPAC decoded according to the first parameter group, thereby improving the MPAC encoding and decoding structure.

[0009] In conjunction with the first aspect, in certain implementations of the first aspect, each parameter group in the plurality of parameter groups corresponds to an MPAC code, and the upper bound value of the approximate joint bound of the MPAC code corresponding to the first parameter group is The following conditions are met: the first parameter group corresponds to is less than or equal to a preset first threshold; or the first parameter group corresponds to Corresponding to the multiple parameter groups The one with the smallest median value; is determined according to the minimum Hamming weight in the MPAC code corresponding to each parameter group and the number of codewords with the minimum Hamming weight, wherein the satisfy d min is the minimum Hamming weight of the MPAC code corresponding to each parameter group, The Hamming weight of the MPAC code corresponding to each parameter group is d min The number of code words, Q (·) is the complement function of the Gaussian cumulative distribution function, R is the code rate of the first MPAC code word sequence, R = K / N, N is the code length of the first MPAC code word sequence, the E b is the signal power per bit, N0 is the noise power spectral density, E b / N0→∞.

[0010] Based on the above scheme, the first parameter group finally determined for encoding is determined according to the approximate joint bound AUB, that is, the upper bound value of the AUB corresponding to each parameter group is calculated for the candidate multiple parameter groups. Also because The smaller the value of is, the better the AUB performance of the MPAC code is. Therefore, the first parameter group corresponds to Corresponding to multiple parameter groups If the median value is the smallest, or is less than or equal to the preset threshold, the performance of the MPAC code determined by the first parameter group is better, thereby improving the MPAC encoding and decoding scheme while being able to better meet the future communication system's requirements for higher reliability of channel coding schemes and obtain better encoding and decoding performance.

[0011] In conjunction with the first aspect, in certain implementations of the first aspect, the d min satisfy Among them, w(g i ) is the Hamming weight of the i-th row in the first polarization transformation matrix corresponding to the first MPAC codeword sequence, For the first set, is a second set, the first set being a set of polarization subchannel subscripts of the information bits included in the first subsequence, and the second set being a set of polarization subchannel subscripts of the information bits included in the second subsequence that directly performs polarization transformation among the K information bits; for The sum of The Hamming weight of the coset of the i-th row of the first polarization transformation matrix is ​​d min The number of code words.

[0012] Based on the above scheme, the upper bound of AUB is It is based on d min and Determined, and d min is the smallest of the Hamming weights of the rows of the first polarization transformation matrix corresponding to the first MPAC codeword sequence with a code length of N, and for and The Hamming weight of the coset of the i-th row of the first polarization transformation matrix is ​​d min Therefore, the number of the lowest weight codewords MWC in the row coset of the first polarization transformation matrix corresponding to each i belonging to the first set and the second set is obtained, that is, the row weight (or Hamming weight) of the coset is d min The number of codewords of the MPAC code corresponding to each parameter group can be obtained by calculating the number of codewords with MWC. The minimum code distance spectrum MWD, that is, the minimum Hamming weight d, can be calculated from the perspective of the coset. min and the number of codewords with minimum Hamming weight Compared with the MWD calculation method implemented by simulation, it has lower computational complexity and can therefore be more effectively applied to the calculation of AUB performance of different MPAC codes, that is, the evaluation of progressive ML performance.

[0013] In conjunction with the first aspect, in some implementations of the first aspect, the The method is determined based on i, the first set, the second set, the third set, the fourth set, and the convolution transformation vector corresponding to each parameter group. The third set is a set of polarization subchannel indexes for frozen bits in the second sequence excluding information bits included in the first subsequence, and the fourth set is a set of polarization subchannel indexes for frozen bits in the first MPAC codeword sequence excluding bits included in the second sequence and information bits included in the second subsequence.

[0014] Based on the above scheme, the Hamming weight of the row in the coset of each i can be d according to the convolution transformation vector corresponding to i, the first set, the second set, the third set, the fourth set and each parameter group. min The number of code words Calculate so that you can then calculate the value of all cosets Calculate the number of MPAC codes corresponding to each parameter group Therefore, it can be more effectively applied to calculate the AUB performance of different MPAC codes, that is, to evaluate the progressive ML performance, and then the first parameter group determined according to the AUB performance is used for MPAC encoding and decoding, thereby improving the MPAC encoding and decoding process.

[0015] In combination with the first aspect, in certain implementations of the first aspect, the first set, the second set, the third set, and the fourth set corresponding to each parameter group are determined according to code rate configuration I and code rate configuration II, the code rate configuration I uses the adjusted RM-Polar criterion, and the code rate configuration II uses the Gaussian GA criterion.

[0016] Based on the above scheme, for each parameter group, the first, second, third, and fourth sets can be determined based on rate profile I and rate profile II. Rate profile I uses the RM-Polar criterion to maximize the minimum Hamming weight of the first and second sets, thereby improving AUB performance. Furthermore, the criteria for rate profile II in MPAC codes are clarified, thereby improving the MPAC coding process.

[0017] In a second aspect, a communication method based on an improved polarization-adjusted convolutional code is provided, the method comprising: receiving a first MPAC codeword sequence and first indication information, the first indication information being used to indicate a first parameter group; performing MPAC decoding on the first MPAC codeword sequence according to the first parameter group; the first MPAC codeword sequence is obtained by performing MPAC encoding on a first sequence to be encoded according to the first parameter group, the first sequence comprising K information bits, K ≥ 1; the first parameter group is determined from a plurality of parameter groups, wherein each parameter group comprises a first value K c and the second value N c, the first value K c is a candidate value of the number of information bits included in the first subsequence that needs to be convolutionally transformed among the K information bits, and the second value N c is a candidate value of the number of bits included in the second sequence obtained after the convolution transformation of the first subsequence, 1≤K c ≤K,N c ≥1, K c ≤N c .

[0018] In conjunction with the second aspect, in certain implementations of the second aspect, each parameter group in the plurality of parameter groups corresponds to an MPAC code, and the upper bound value of the approximate joint bound of the MPAC code corresponding to the first parameter group is The following conditions are met: the first parameter group corresponds to is less than or equal to a preset first threshold; or the first parameter group corresponds to Corresponding to the multiple parameter groups The one with the smallest median value; is determined according to the minimum Hamming weight in the MPAC code corresponding to each parameter group and the number of codewords with the minimum Hamming weight, wherein the satisfy d min is the minimum Hamming weight of the MPAC code corresponding to each parameter group, The Hamming weight of the MPAC code corresponding to each parameter group is d min The number of code words, Q (·) is the complement function of the Gaussian cumulative distribution function, R is the code rate of the first MPAC code word sequence, R = K / N, N is the code length of the first MPAC code word sequence, the E b is the signal power per bit, N0 is the noise power spectral density, E b / N0→∞.

[0019] In conjunction with the second aspect, in certain implementations of the second aspect, the d min satisfy Among them, w(g i ) is the Hamming weight of the i-th row in the first polarization transformation matrix corresponding to the first MPAC codeword sequence, For the first set, is a second set, the first set being a set of polarization subchannel subscripts of the information bits included in the first subsequence, and the second set being a set of polarization subchannel subscripts of the information bits included in the second subsequence that directly performs polarization transformation among the K information bits; for The sum of The Hamming weight of the coset of the i-th row of the first polarization transformation matrix is ​​d min The number of code words.

[0020] In conjunction with the second aspect, in some implementations of the second aspect, the is determined based on i, the first set, the second set, the third set, the fourth set, and the convolution transformation vector corresponding to each parameter group, wherein the third set is a set of polarization subchannel indexes for frozen bits in the second sequence excluding information bits included in the first subsequence, and the fourth set is a set of polarization subchannel indexes for frozen bits in the first MPAC codeword sequence excluding bits included in the second sequence and information bits included in the second subsequence.

[0021] In combination with the second aspect, in certain implementations of the second aspect, the first set, the second set, the third set, and the fourth set corresponding to each parameter group are determined according to code rate configuration I and code rate configuration II, the code rate configuration I uses the adjusted RM-Polar criterion, and the code rate configuration II uses the Gaussian GA criterion.

[0022] In combination with the second aspect, in certain implementations of the second aspect, it is characterized in that the code rate configuration I uses the adjusted RM-Polar criterion, and the code rate coordination II uses the Gaussian GA criterion.

[0023] In a third aspect, a communication device is provided, configured to execute the method provided by any of the above aspects or implementations thereof. Specifically, the device may include units and / or modules, such as a processing unit and / or a transceiver unit, configured to execute the method provided by any of the above aspects or implementations thereof.

[0024] In one implementation, the apparatus is a transmitting device or a receiving device. When the apparatus is a transmitting device or a receiving device, the transceiver unit may be a transceiver, an input / output interface, or a communication interface; and the processing unit may be at least one processor. Optionally, the transceiver is a transceiver circuit. Optionally, the input / output interface is an input / output circuit.

[0025] In another implementation, the apparatus is a chip, chip system, or circuit used in a transmitting device or a receiving device. When the apparatus is a chip, chip system, or circuit used in a transmitting device or a receiving device, the transceiver unit may be an input / output interface, interface circuit, output circuit, input circuit, pin, or related circuit on the chip, chip system, or circuit; and the processing unit may be at least one processor, processing circuit, or logic circuit.

[0026] In a fourth aspect, a communication device is provided, comprising: a memory for storing programs; and at least one processor for executing computer programs or instructions stored in the memory to perform the method provided by any one of the above aspects or its implementation.

[0027] In one implementation, the apparatus is a transmitting end device or a receiving end device.

[0028] In another implementation, the apparatus is a chip, a chip system, or a circuit used in a transmitting device or a receiving device.

[0029] In a fifth aspect, a communication device is provided, comprising: at least one processor and a communication interface, wherein the at least one processor is configured to retrieve a computer program or instruction stored in a memory through the communication interface to execute the method provided by any of the above aspects or implementations thereof. The communication interface may be implemented in hardware or software.

[0030] In one implementation, the device further includes the memory.

[0031] In a sixth aspect, a processor is provided for executing the methods provided in the above aspects.

[0032] For the operations such as sending and acquiring / receiving involved in the processor, unless otherwise specified, or if they do not conflict with their actual functions or internal logic in the relevant descriptions, they can be understood as operations such as processor output, reception, and input, or as sending and receiving operations performed by the radio frequency circuit and antenna. This application does not limit this.

[0033] In a seventh aspect, a computer-readable storage medium is provided, which stores a program code for execution by a device, wherein the program code includes a method for executing any one of the above aspects or its implementation.

[0034] In an eighth aspect, a computer program product comprising instructions is provided, which, when run on a computer, enables the computer to execute the method provided by any one of the above aspects or its implementation.

[0035] In a ninth aspect, a chip is provided, comprising a processor and a communication interface, wherein the processor reads instructions stored in a memory through the communication interface and executes the method provided by any one of the above aspects or implementations thereof. The communication interface may be implemented in hardware or software.

[0036] Optionally, as an implementation method, the chip also includes a memory, in which a computer program or instruction is stored, and the processor is used to execute the computer program or instruction stored in the memory. When the computer program or instruction is executed, the processor is used to execute the method provided by any of the above aspects or its implementation methods.

[0037] When the method provided in this application is executed by a chip, this application does not limit the number of chips that implement the method. For example, the method can be executed by one chip or by two or more chips. Furthermore, when the number of chips implementing the method of this application is two or more, the chip manufacturers are not limited and can be the same manufacturer or different manufacturers.

[0038] In a tenth aspect, a communication system is provided, comprising at least one of the transmitting device or the receiving device described above.

[0039] In an eleventh aspect, a computer program is provided, which, when executed on a computer, enables the method provided by any one of the above aspects or its implementation to be executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] FIG1 is a schematic diagram of a network architecture applicable to an embodiment of the present application.

[0041] Figure 2 is a block diagram of the Polar code encoding process.

[0042] FIG3 is a block diagram of the PAC code encoding process.

[0043] Figure 4 shows (N,K)-(N c ,K c )Block diagram of the MPAC code encoding process.

[0044] FIG5 is a schematic diagram of the process of constructing the MPAC code rate configuration subscript set.

[0045] FIG6 is a schematic diagram of the information transmission process.

[0046] FIG7 is a schematic flowchart of a communication method 700 based on MPAC codes provided in this application.

[0047] FIG8 is a schematic flow chart of the optimization design method of the MPAC code of the present application.

[0048] FIG9 is a schematic diagram of a channel selection scheme for MPAC codes.

[0049] FIG10 is a Wayne diagram of the sets involved in the coset of coset-first i on [i+1,N-1].

[0050] Figure 11 shows the MPAC code with (N, K) = (128, 64) at different (N c ,Kc )AUB performance diagram under .

[0051] FIG12 is a performance comparison of FER and normalized complexity of different coding schemes with (N, K) = (128, 64).

[0052] Figure 13 shows the MPAC code with (N, K) = (256, 163) using different parameters (N c ,K c ) under AUB performance.

[0053] FIG14 is a performance comparison of FER and normalized complexity of different coding schemes for (N, K) = (256, 163).

[0054] FIG15 is a schematic block diagram of a communication device 1000 provided in an embodiment of the present application.

[0055] FIG16 is a schematic block diagram of a communication device 2000 provided in an embodiment of the present application.

[0056] FIG17 is a schematic block diagram of a chip system 3000 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] To facilitate understanding of the embodiments of the present application, the following points are explained before introducing the embodiments of the present application:

[0058] The various numerical designations such as "first," "second," and so on are merely for convenience of description and are not intended to limit the scope of the embodiments of this application, for example, to distinguish between different messages or different information. "Pre-defining" or "pre-storing" can be implemented by pre-saving corresponding codes, tables, or other methods that can be used to indicate relevant information in the device. This application does not limit the specific implementation method. The "protocol" referred to may refer to a standard protocol in the communications field, such as the Long Term Evolution (LTE) protocol, the New Radio (NR) protocol, and related protocols used in future communications systems. This application does not limit this. Words such as "exemplary," "for example," "illustratively," and "as (another) example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described in this application as an "example" should not be construed as preferred or advantageous over other embodiments or designs. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized. "At least one" means one or more, and "a plurality" means two or more. "At most one" or "at most one" means one or zero. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c. Where a, b and c can be single or multiple. The description involving network element A sending a message, information or data to network element B, and network element B receiving a message, information or data from network element A, is intended to indicate to which network element the message, information or data is to be sent, and does not limit whether they are sent directly or indirectly via other network elements. Descriptions such as "when...", "in the case of...", "if...", and "if" all mean that the device will take corresponding actions under certain objective circumstances. They do not limit the time, nor do they require the device to make judgments when implementing them, nor do they imply the existence of other limitations.

[0059] In addition, the network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0060] The following describes a communication system that can be applied to the embodiments of the present application:

[0061] The technical solutions of the embodiments of the present application can be applied to various communication systems, including but not limited to: global system of mobile communication (GSM) system, enhanced data rate for GSM evolution system (EDGE), fifth generation (5G) system or new radio (NR) system, LTE system, long term evolution-advanced (LTE-A) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD) system, wideband code division multiple access (WCDMA) system, code division multiple access (CDMA) system, time division-synchronization code division multiple access system (TD-SCDMA), etc. It can also be applied to future communication systems, such as the sixth generation mobile communication system. Furthermore, the present invention can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems. Furthermore, the present invention can also be extended to similar wireless communication systems, such as wireless-fidelity (Wi-Fi), worldwide interoperability for microwave access (WIMAX), and communication systems related to the 3rd Generation Partnership Project (3GPP), without limitation.

[0062] A communication system applicable to embodiments of the present application may include one or more transmitting devices and one or more receiving devices. Optionally, one of the transmitting device and the receiving device may be a terminal device, and the other may be a network device. Optionally, both the transmitting device and the receiving device may be terminal devices. Optionally, both the transmitting device and the receiving device may be network devices.

[0063] The technical solution in this application will be described below with reference to the accompanying drawings.

[0064] Figure 1 is a schematic diagram of a network architecture applicable to an embodiment of the present application. As shown in Figure 1, the embodiment of the present application can be applied to both uplink data transmission and downlink data transmission. Figure 1 only takes uplink data transmission or downlink data transmission between a network device and two terminal devices (such as terminal device 1 and terminal device 2) as an example. In uplink data transmission, the transmitting device in this article is a terminal device, and the receiving device is a network device; conversely, in downlink data transmission, the transmitting device is a network device, and the receiving device is a terminal device. In addition, the applicability of the embodiments of the present application in other communication scenarios is not limited. For example, it can also be applied to sidelink communications.

[0065] The terminal devices in the embodiments of the present application include various devices with wireless communication functions, which can be used to connect people, objects, machines, etc. The terminal devices can be widely used in various scenarios, such as: cellular communication, D2D, V2X, peer to peer (P2P), M2M, MTC, IoT, virtual reality (VR), augmented reality (AR), industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city drones, robots, remote sensing, passive sensing, positioning, navigation and tracking, autonomous delivery, etc. The terminal device can be a terminal in any of the above scenarios, such as an MTC terminal, an IoT terminal, etc. The terminal device may be a user equipment (UE) of the third generation partnership project (3GPP) standard, a terminal, a fixed device, a mobile station device or a mobile device, a subscriber unit, a handheld device, a vehicle-mounted device, a wearable device, a cellular phone, a smart phone, a session initialization protocol (SIP) phone, a wireless data card, a personal digital assistant (PDA), a computer, a tablet computer, a notebook computer, a wireless modem, a handheld device (handset), a laptop computer, a computer with wireless transceiver function, a smart book, a vehicle, a satellite, a global positioning system (GPS) device, a target tracking device, an aircraft (such as a drone, a helicopter, a multi-copter, a quadcopter, or an airplane), a ship, a remote control device, a smart home device, an industrial device, or a device built into the above-mentioned device (such as a communication module, a modem or a chip in the above-mentioned device), or other processing devices connected to a wireless modem. For the sake of convenience of description, the terminal device will be described below by taking the terminal or UE as an example.

[0066] It should be understood that in some scenarios, a UE can also be used to act as a base station. For example, a UE can act as a scheduling entity that provides sidelink signals between UEs in scenarios such as V2X, D2D, or P2P.

[0067] In the embodiments of the present application, the device for implementing the function of the terminal device can be the terminal device, or it can be a device that can support the terminal device to implement the function, such as a chip system or chip, which can be installed in the terminal device. In the embodiments of the present application, the chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0068] The network device in the embodiments of the present application may be a device for communicating with a terminal device, and may also be referred to as an access network device or a radio access network device. For example, the network device may be a base station. The network device in the embodiments of the present application may refer to a radio access network (RAN) node (or device) that connects a terminal device to a wireless network. The base station can broadly cover various names as follows, or be replaced with the following names, such as: NodeB, evolved NodeB (eNB), next generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master station, secondary station, multiple radio access technologies (multi-RAT) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), centralized unit (CU), distributed unit (DU), radio unit (RU), positioning node, RAN intelligent controller (RIC), etc. A base station can be a macro base station, a micro base station, a relay node, a donor node, or the like, or a combination thereof. A base station can also refer to a communication module, a modem, or a chip used to be set in the aforementioned device or apparatus. A base station can also be a mobile switching center, a device that performs base station functions in D2D, V2X, and M2M communications, a network-side device in a future communication network, or a device that performs base station functions in a future communication system. A base station can support networks with the same or different access technologies. The embodiments of this application do not limit the specific technology and specific device form used by the network equipment.

[0069] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move based on the location of the mobile base station. In other examples, a helicopter or drone can be configured to act as a device that communicates with another base station.

[0070] In some deployments, the network device mentioned in the embodiments of the present application may include a CU, a DU, a CU and a DU, or a CU control plane (centralized unit-control plane, CU-CP) and a CU user plane (centralized unit-user plane, CU-UP) as well as a DU node. For example, the network device may include a gNB-CU-CP, a gNB-CU-UP, and a gNB-DU.

[0071] In some deployments, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, and different RAN nodes respectively implement part of the functions of the base station. For example, the RAN node can be CU, DU, CU-CP, CU-UP, or RU, etc. The CU and DU can be set separately, or they can be included in the same network element, such as the BBU. The RU can be included in a radio frequency device or radio frequency unit, such as an RRU, AAU or RRH. In one possible design, the processing unit for implementing the baseband function in the BBU is called a baseband high layer (BBH) unit, and the processing unit for implementing the baseband function in the RRU / AAU / RRH is called a baseband low layer (BBL) unit. In different systems, CU (or CU-CP and CU-UP), DU or RU may also have different names, but those skilled in the art can understand their meanings. For example, the radio access network may also be an open radio access network (O-RAN) architecture. In the ORAN system, the CU may also be referred to as an O-CU (open CU), the DU may also be referred to as an O-DU, the CU-CP may also be referred to as an O-CU-CP, the CU-UP may also be referred to as an O-CU-UP, and the RU may also be referred to as an O-RU. Any of the CU (or CU-CP, CU-UP), DU, and RU in this application may be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0072] In the embodiments of the present application, the device for implementing the function of the network device can be the network device, or it can be a device that can support the network device to implement the function, such as a chip system or chip, which can be installed in the network device. In the embodiments of the present application, the chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0073] Network devices and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on the water surface; they can also be deployed on aircraft, balloons and satellites in the air. The embodiments of this application do not limit the scenarios in which network devices and terminal devices are located. In addition, terminal devices and network devices can be hardware devices, or they can be software functions running on dedicated hardware, software functions running on general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities including dedicated or general-purpose hardware devices and software functions. This application does not limit the specific forms of terminal devices and network devices.

[0074] The scenarios in which this application can be applied include, but are not limited to: enhanced mobile broadband (eMBB) scenarios, ultra-reliable low latency communication (URLLC) scenarios, massive IoT communication / massive machine type communication (mMTC) scenarios, uplink centric broadband communication (UCBC) scenarios, real-time broadband communication (RTBC) scenarios, etc., without limitation.

[0075] It should be noted that some embodiments herein use the 5G system as an example to describe specific solution details. It is understood that when this solution is applied to other communication systems, such as the LTE system or future communication systems, the messages, channels, or information in the solution can be replaced with messages, channels, or information in other communication systems that can implement corresponding functions, and this application does not limit this.

[0076] To facilitate understanding of the embodiments of the present application, several concepts or terms involved in the embodiments of the present application are briefly explained. The concepts or terms introduced below are explained based on the concepts or terms specified in the reference protocol, but this does not mean that the embodiments of the present application can only be applied to existing systems. The concepts or terms involved in the embodiments of the present application can be applied to future systems. The specific names of the concepts or terms (for example, concepts or terms involving functional descriptions) can be adjusted as future systems develop.

[0077] 1. Polar code

[0078] Polar code is proposed based on the channel polarization phenomenon. Through the channel merging and splitting process, the original N independent binary input discrete memoryless channels (BI-DMC) W will become N polarization sub-channels with different polarization degrees. Specifically, when the code length (or bit dimension, bit length, number of bits, etc.) N is large enough, It will become a noiseless channel or a full noise channel by By transmitting information bits and frozen bits separately, reliable transmission of information can be achieved.

[0079] Figure 2 is a block diagram of the Polar code encoding process. As shown in Figure 2, for a Polar code with an input information bit of K and an output code length of N, where code length N = 2 n , given the input information vector (or information bit sequence, information bit vector, information sequence, etc.) is and To express The vector dimension is 1×K. The information vector is first configured with a code rate to obtain a message vector that carries information bits. and To represent the vector (or sequence) carrying the information bits The dimension is 1×N. Specifically, the subscript set [1, N] of the polarimetric subchannel is divided into information sets according to different criteria, such as Gaussian approximation (GA), RM (Reed-Muller) criterion, RM-polar criterion, etc. and frozen collections Among them, the information collection It can be understood as an information vector In the message vector The set of positions in , so the information set The length is K, which is expressed as The frozen set is the message vector Information collection The set is composed of positions other than The length is NK, which can be expressed as Information Collection and frozen collections The indexed polarization sub-channels will be used to transmit information bits and frozen bits 0 respectively, so It can be expressed as in,

[0080] In addition, the Polar code decoding algorithm successive cancellation (SC) is a low-complexity decoding scheme that has been proven to be able to achieve channel capacity when the code length is long enough.

[0081] 2. PAC code

[0082] PAC codes are coset codes that concatenate a rate-1 convolutional code with a Polar code and pre-select the frozen bits before the convolutional coding, thereby redistributing channel capacity. With the assistance of decoders close to ML, such as Fano, PAC codes with medium and short code lengths can effectively approach the finite code length performance bound.

[0083] Figure 3 is a flowchart of the PAC code encoding process. As shown in Figure 3, the PAC code encoding starts with the code rate configuration, and the information length (or information bit dimension, information bit length, number of information bits, etc.) is the information vector K. After the bit rate configuration, Place to carrier vector Information collection In the corresponding position, that is is the carrier vector Used for transmission The set of positions of . And the carrying vector Information collection The positions other than the ones are frozen bits, and the frozen bits are set to 0, that is, Then, the Through the convolution matrix G with a code rate of 1 c Get the codeword vector The G c It can also be called the generator matrix. Since the code rate of the convolution transform is 1, G c It can be expressed as an upper triangular Toeplitz matrix, that is

[0084] The codeword vector after convolution transformation According to the formula It can be generated, or it can be generated bit by bit using the shift register method of algorithm #1. Table 1 is a schematic diagram of the single-bit convolutional coding process implemented by algorithm #1, as follows:

[0085] Table 1 Schematic diagram of the implementation process of algorithm #1

[0086] Furthermore, the codeword vector after convolution transformation Through the polarization transformation matrix G p Get the codeword of the PAC code with code length N The generation formula is expressed as Therefore, the polarization transformation matrix and Where F is the kernel matrix of the Polar code, Expressed as a Kronecker product operation.

[0087] It can be seen that the encoding scheme of the PAC code can be determined by the parameters N, K, , g(x) is determined, where N is the codeword length obtained after PAC encoding, K is the length of the input information vector, is a set of positions used to transmit information vectors in the vector obtained after the information vector is configured with bit rate. is the frozen position in the vector obtained after the information vector is rate-configured, and g(x) is the convolution transformation g(x) = g0 + g1x + ··· + g t x t The generating polynomial of , or it can be expressed in vector form as Or it can be expressed in the form of a matrix, that is, G c .

[0088] PAC codes use a concatenated coding scheme. The addition of convolutional transforms effectively improves the codeword structure of short and medium-length Polar codes, significantly reducing the number of low-repetition codewords. From a channel capacity perspective, convolutional transforms redistribute polarization channel capacity, allowing polarization subchannels that originally transmitted frozen bits to also carry some transmission load, thereby fully utilizing channel capacity.

[0089] The encoding of PAC code involves the process of code rate configuration, or the process of information bit selection, that is, for the information set Different code rate configuration methods will affect the performance of the PAC code. The following will introduce two typical code rate configuration design methods.

[0090] (1) Polar code-like construction method

[0091] The Polar code-like construction method uses the same design principles as traditional Polar codes, selecting information bits based on the conditions of the polarized subchannels. This method calculates and ranks the polarized subchannel conditions, then selects the index values ​​corresponding to polarized subchannels with high channel capacity or low error probability as information bits. Existing Polar code construction methods, such as the Bhattacharyya parameter construction method and the Gaussian approximation (GA) construction method, can be applied to PAC codes. The information bit selection scheme designed is the same as that for Polar codes with the same parameters.

[0092] (2) RM (Reed Muller) code construction method

[0093] The RM-like code construction method generates the matrix G based on the polarization transformation p The Hamming weight of the row (or row weight) is used to determine the information bit. Before introducing the specific design method, the RM weight b(i) is defined first. p The RM weight b(i) of the i-th row is defined as the number of 1s in the binary representation of i, where 0≤i≤N-1. For example, the binary representation of 11 is 1011, where the number of 1s is 3, then b(11)=3. The polarization transformation matrix G p The row redistribution satisfies the following two properties:

[0094] Property 1: Given an N×N order polarization transformation matrix G p Any i-th row g i , the g i The weight of a row is ω(g i )=2 b(i) , where 0≤i≤N-1.

[0095] Property 2: Given an N×N order polarization transformation matrix G p , the row weight is 2 j The number of rows is Where n=log2(N), 0≤j≤n.

[0096] The RM-like code construction method transforms the polarization matrix G according to the RM weight value. p The rows of RM are divided and the vector position corresponding to the row with large RM weight is selected to transmit the information bit. For example, assuming a given threshold T γ =2 γ , 0≤γ≤n, select the row weight greater than or equal to T according to the RM code construction method γ The index value corresponding to the row is used as the information bit, then the information set According to Property 2, the size of the information bit set

[0097] The PAC code constructed according to the RM-like code construction method has excellent minimum weight distribution (MWD) characteristics, that is, the minimum Hamming distance is large or the number of minimum weight codewords is small, and has extreme performance that can approach the performance bound of finite code length.

[0098] 3. MPAC code

[0099] Figure 4 shows (N,K)-(N c ,K c )MPAC code encoding flow chart. As shown in Figure 4, the information vector First divided into and Two sub-information vectors are expressed as in, Next, similar to the encoding process of the PAC code, the sub-information vector After the code rate configuration I, the bearer vector is obtained vector Then the code word is obtained by convolution transformation preprocessing with a code rate of 1 It is expressed as Similar to PAC code, the convolution transformation matrix G c ' can also be determined by the generating polynomial g(x). It can be seen that MPAC code adopts the idea of ​​"partial convolution", that is, only the information length K c Information vector Perform convolution transformation, and the codeword length after convolution transformation is N c Unlike PAC codes, the order of the convolution transform matrix of MPAC codes has changed, that is, the dimension of the convolution transform matrix of MPAC is N. c ×N c It is understandable that the parameter N c The dimension of the convolution transformation matrix of the MPAC code is determined, and the parameter K c The length of the information vector for convolution transformation, or the number of information bits, is determined. Codeword after convolution transformation and another sub-information vector are transmitted together via the polarization channel under the effect of code rate configuration II. Specifically, the vector and The bearer vector obtained after processing the code rate configuration II is Then the final codeword is obtained through polarization transformation Similar to the PAC code, the polarization transformation process is expressed as As can be seen, an information vector with an information length of K, after undergoing the MPAC code encoding process, ultimately yields a codeword with a code length of N. Similar to Polar and PAC codes, the rate configuration operation can construct a short vector into a long vector. The short vector is generally referred to as the "information vector," while the long vector is generally referred to as the "bearing vector." The specific process of rate configuration depends on the position subscript set of the polarization subchannels for the rate configuration. The rate configuration scheme for MPAC coding consists of the GA criterion and the improved RM-Polar (iRMP) criterion. The following describes the MPAC code rate configuration schemes I and II, respectively.

[0100] (1) Bitrate Configuration II

[0101] Code rate configuration II adopts the GA-based polarization channel reliability criterion, which aims to obtain three sets of position subscripts with different reliability, which are used to place the sub-information vectors for direct transmission. Codeword after convolution transformation and frozen bit sequences

[0102] For example, it is assumed that after the GA criterion, the reliability order of the position subscripts of the polarization subchannels is (j0, j1, ..., j N-1 ) GA , that is, j0 to j N-1 satisfy Among them, j0 to j N-1 are the position subscript indices of the polarization subchannel, which can be understood as the transmission sub-information vector Codeword after convolution transformation and frozen bit sequences The polarization subchannel position index of . represents the mean of the log likelihood ratio (LLR) values ​​estimated by the GA method, The larger the value, the more polarization channels The more reliable. On this basis, after sorting in ascending order according to the GA criterion, the KK with the highest reliability is obtained. c +N c The polarization sub-channel indexes form a set Next, you can determine The less reliable N c Positions constitute a set The bearer vector obtained after code rate configuration II Corresponding to the set The position of the convolution transformation vector will be placed Right now Will be gathered Transmission is carried out in the corresponding polarization channel. The polarization sub-channel corresponding to the obtained set is used to transmit the sub-information vector and The corresponding polarization sub-channel is used to transmit the frozen bit 0 to ensure reliable information transmission. It can be understood that Represents the carrying vector Does not correspond to a set location.

[0103] (2) Bitrate Configuration I

[0104] Code rate configuration I further determines the sub-information vector for convolution transformation In the carrier vector The purpose is to ensure that the MWD characteristics of the constructed MPAC code are not too poor. Specifically, the code rate configuration I uses the RM weight b(i) to set The corresponding polarization sub-channels are reordered according to the iRMP criterion, and K is obtained. c The polarimetric subchannel subscript.

[0105] For example, the polarization transformation matrix G p The row weight of the i-th row satisfies ω(g i )=2 b(i) , for the set The process of reordering the polarization subchannels corresponding to the polarization subchannel subscript indices in is equivalent to giving priority to the polarization subchannel with heavier row weight. For example, when b(i1)>b(i2), the polarization subchannel corresponding to i1 is given priority. When the row weights are the same, for example, b(i1)=b(i2), the subchannel with higher reliability is selected. For example, when When i1 is selected, the polarization sub-channel corresponding to i1 is selected. It can be understood that in the above example, i1 always has a higher priority than i2. The code rate configuration I will Re-sort, For the set The result of sorting the position subscripts in ascending order according to the iRMP criterion. Then from the set Prioritize K that meets iRMP criteria c positions, represented by a set and The elements in the collection are the position index results after sorting in ascending order. The polarization subchannel corresponding to the subscript position index in the set is used to transmit the sub-information vector

[0106] It should be noted that i in the above description represents the position of the polarized subchannel, a natural number starting from 1, while j is the position subscript index, a natural number starting from 0. Therefore, the subscripts of the same subchannel positions represented by j and i differ by 1. For example, to represent the first subchannel position, i1 and j0 can be used, respectively.

[0107] Figure 5 is a schematic diagram of the MPAC code rate configuration subscript set construction process. As shown in Figure 5, the code rate configuration II can sort the N polarization subchannels in ascending order according to the GA criterion and determine the KK with the highest reliability. c +N c The position subscripts corresponding to the polarization subchannels constitute the set Then you can Determined to be less reliable N c The position subscripts corresponding to the polarization subchannels constitute the set The bit rate configuration I can be used to set the N in c The position subscripts corresponding to the polarization subchannels are rearranged in ascending order, and the K c Positions constitute a set After the encoding framework of the above MPAC code is defined, the mapping function used in the decoding process can be pre-calculated. For example, given the set Sort the elements from small to large to construct an ordered vector And define the operation Representing a collection Any element p in i In an ordered vector The subscript position in Similarly, the set Defining a mapping function

[0108] Based on the PAC code encoding and decoding scheme, the MPAC code encoding and decoding scheme improves the PAC code encoding and decoding through two parts: the "partial convolution" coding structure and the "hybrid strategy" decoding algorithm, which can achieve better decoding performance than the Polar code. MPAC uses the hybrid Fano-SC (HFSC) decoding method to effectively make up for the defect that the PAC code scheme with a length of 512 codes is difficult to achieve ideal decoding performance under the limited decoding complexity.

[0109] 4. Information transmission process

[0110] Figure 6 is a schematic diagram of the information transmission process. As shown in Figure 6, information is sent from the source, and after processing such as source coding, channel coding, modulation, air interface transmission, demodulation, channel decoding, source decoding, etc., it arrives at the destination, completing the information transmission from the source to the destination. Among them, the processing shown in the first half of Figure 6 (including source coding, channel coding, modulation, etc.) is performed by the transmitting end device, and the processing shown in the second half of Figure 6 (including source decoding, channel decoding, demodulation, etc.) is performed by the receiving end device. This application mainly relates to the channel coding and channel decoding processing part shown in Figure 6. The dotted box in Figure 6 shows the process from channel coding to channel decoding. Channel coding is responsible for encoding the bits generated by the source, and then after modulation, sending the modulation symbols through the noisy channel to the receiving end for demodulation, and then performing channel decoding. The channel part is located between demodulation and source decoding, and is responsible for recovering the source bit stream.

[0111] As can be seen from the above, MPAC codes achieve a better compromise between decoding performance and decoding complexity. This compromise is reflected in the significant decoding performance gain compared to traditional polar codes and SC decoding schemes. Furthermore, compared to traditional PAC codes and Fano decoding schemes, MPAC codes achieve lower decoding complexity, thus achieving superior decoding performance and decoding complexity under complexity constraints. Therefore, using MPAC codes for coding and decoding can achieve both good decoding performance and low complexity.

[0112] From the above description of MPAC, we can see that MPAC codes use the concept of "partial convolution", that is, the input information vector is divided into two sub-information vectors, one of which is used for convolution transformation and the other is directly polarized. Therefore, the encoding process of MPAC codes involves the number of information bits that undergo convolution transformation, that is, the information length K of the sub-information vector that undergoes convolution transformation. c Determination of the code length N of the codeword obtained after convolution transformation c That is, the MPAC code encoding involves the parameters used for convolution transformation (hereinafter referred to as convolution parameters) (N c ,K c ) is determined. Relatively speaking, the MPAC code decoding process also needs to clarify the convolution parameters (N c ,K c ) can be decoded. However, the convolution parameters (N c ,K c There is no clear criterion or method for selecting the convolution parameter (N) for MPAC codes. However, the existing PAC code construction scheme cannot be directly applied to MPAC codes because PAC codes have different structures from MPAC codes.c ,K c ) needs to be resolved urgently.

[0113] Based on this, the present application proposes a communication method based on an improved polarization adjustment convolutional code, which can select a plurality of candidate information lengths K c Sum code length N c In the combination, an information length and a code length are determined as parameters for MPAC partial convolutional coding. The information length and code length are two values ​​in the first parameter group, so that MPAC encoding can be performed on the information bit sequence to be encoded to obtain a first MPAC codeword sequence. Furthermore, the first information length and first code length determined in the first parameter group are transmitted so that the obtained first MPAC codeword sequence can subsequently be MPAC decoded according to the first parameter group, thereby improving the MPAC coding and decoding structure.

[0114] Figure 7 is a schematic flow chart of a communication method 700 based on MPAC codes provided by the present application. As shown in Figure 7 , the method includes steps S710 to S750, which are described in detail below.

[0115] S710: The transmitting end device obtains an information bit sequence to be encoded.

[0116] If a transmitting device needs to communicate with a receiving device, that is, if the transmitting device needs to send a signal to the receiving device, the transmitting device must first obtain the information bit sequence corresponding to the signal sent to the receiving device. Correspondingly, the receiving device can receive the information bit sequence from the transmitting device.

[0117] The transmitting device obtaining the information bit sequence may refer to the transmitting device performing source encoding on source symbols to generate the information bit sequence. The transmitting device obtaining the information bit sequence may also refer to the transmitting device obtaining (e.g., receiving) the information bit sequence from another communication device. This information bit sequence is an example of a first sequence.

[0118] S720: The transmitting device determines a first parameter group from multiple parameter groups.

[0119] Each parameter group includes a first value Kc and a second value Nc, wherein the first value Kc is a candidate value for the number of information bits included in the first subsequence of K information bits that need to be convolutionally transformed, and the second value Nc is a candidate value for the number of bits included in the second sequence obtained after the first subsequence is convolutionally transformed, 1≤Kc≤K, Nc≥1, Kc≤Nc. The following describes in detail how to determine the first parameter group from multiple parameter groups. (N c ,K c ) is an exemplary symbolic representation of a parameter group.

[0120] It should be noted that the sub-information vectors that need to be convolved in the MPAC code described in this application are is an example of the first subsequence, the codeword after convolution transformation As an example of the second sequence, the sub-information vector directly subjected to polarization transformation in the MPAC code is is an example of the second subsequence.

[0121] The first information length and the first code length are determined according to the first criterion. The first information length and the first code length are used for convolution coding in the MPAC code. The first information length and the first code length are an example of the first value and the second value in the first parameter group.

[0122] Specifically, according to the given code length N and the information length K of the information bit sequence, or in other words, given MPAC code parameters (N, K), a candidate code length and information length combination can be determined. The candidate code length and information length can be used to construct the MPAC code. The candidate code length and information length can also be called the convolution parameter (N) used for convolution coding in the MPAC code. c ,K c ). Then, according to the first criterion, a first information length and a first code length that meet the first condition are determined from the candidate code lengths and information lengths. The candidate code length and information length are examples of candidate first values ​​and candidate second values ​​included in each parameter group in the multiple parameter groups.

[0123] Since the given code length is N, the value range of the candidate code length is 1 to N, that is, the parameter N c It can be any natural number from 1 to N. Since the given message length is K, the value range of the candidate message length is 1 to K, that is, the parameter K c It can be any natural number from 1 to K. It can be understood that the code length is greater than or equal to the information length, so the candidate convolution parameter (N c ,K c )There are a total of (N-K+1)×K types.

[0124] For example, when the given code length is 8 and the information length is 4, the transmitting device will obtain an MPAC code with parameters (8, 4) after encoding by the encoder. Then the candidate parameters (N c ,K c ) can be (8,1), (8,3), (4,2), (3,2), etc. For the sake of brevity, they are not listed here one by one.

[0125] The first criterion may be an approximate union bound (AUB) performance criterion, which may be used to evaluate the ML performance of a code. The AUB criterion may be used to evaluate the ML performance of a code as follows:

[0126] For a linear block code with input parameters (N, K), under binary phase shift keying (BPSK) modulation and a binary input-additive white Gaussian noise (BI-AWGN) channel, the frame error rate (FER) performance upper bound of a soft-decision ML decoder can be estimated as follows:

[0127] Where R is the code rate of the (N, K) code, R = K / N, E b / N0 represents the signal power per bit E b The ratio of Q(·) to the noise power spectral density N0 can be considered as the signal-to-noise ratio (SNR) to measure the quality of the channel conditions. Q(·) is the complement of the Gaussian cumulative distribution function, and A d It is expressed as the number of code words with Hamming weight d in the code. This upper bound is also called the Union Bound. b When / N0→∞, that is, when the SNR is very high, the upper bound can be approximated as

[0128] Among them, d min is the minimum Hamming weight of the code, is the Hamming weight d min The number of codewords, that is, the number of minimum weight codewords (MWC), these two parameters are called the minimum code distance spectrum (MWD) of the code, which will directly affect the above approximate performance bound, referred to as the approximate joint bound (AUB).

[0129] It should be understood that AUB can be used to evaluate the ML performance of the constructed MPAC code, and the upper bound of AUB can be approximately The smaller the value, the better the ML performance of the constructed MPAC code. The size of the parameter d min and Therefore, the ML performance of the constructed MPAC code will be affected by the parameter d min and impact.

[0130] Therefore, the performance priority principle of AUB can be converted into the following two design rules:

[0131] (1) Minimum Hamming weight d of MPAC code min Make it as big as possible;

[0132] (2) In d min When they are equal, the number of MWCs As small as possible.

[0133] FIG8 is a schematic flow chart of the optimization design method of the MPAC code of the present application. As shown in FIG8, given the code length N and the information dimension K, the code rate configuration process and the convolution parameter (N c ,K c ), this method can be applied to the encoding of explicitly constructing MPAC codes or MPAC-like codes. Since the process of rate configuration and the determination of convolution parameters will affect the performance of the constructed MPAC code at the same time, joint optimization is required to obtain MPAC-like codes with excellent performance. However, due to the limitations of the large number and complexity of variables considered in the joint optimization and the lack of theoretical characterization, a step-by-step optimization strategy will be adopted. As can be seen from Figure 8, the rate configuration I is first optimized and designed, and then the convolution parameters (N c ,K c ). That is, it will be done in two steps:

[0134] The first step is to determine the bitrate configuration I using the iRMP criterion to maximize d min ;

[0135] In one possible implementation, the minimum Hamming weight can be d min The part is used to determine the position of the sub-information vector entering the convolution transformation in the carrier vector. For example, the minimum Hamming weight is 2 7 There are 1000 corresponding subscript positions, and 500 subscript positions are selected from them to determine the position of the sub-information vector entering the convolution transform and after the code rate configuration I is passed, in the carrying vector.

[0136] The second step is to compare the AUB performance of the MPAC code constructed by the candidate information length and code, that is, to compare the candidate first parameter group (N) for MPAC convolutional coding. c ,K c ) * , that is, determine the candidate (N c ,K c ) satisfies the first condition in the first information length and the first code length, the first code length is (N c ,K c )* N in c , the first information length is (N c ,K c ) * K in c .

[0137] In a possible implementation, the first condition may be a candidate (N c ,K c ) corresponds to the upper limit of AUB At least one of the median values ​​is less than or equal to the first threshold Any of the values The value corresponding to (N c ,K c ) as the first information length and the first code length, that is, the first information length and the first code length are candidates with better AUB performance (N c ,K c ), or the first information length and the first code length corresponding to The value is less than or equal to the preset first threshold. Alternatively, the first condition is a candidate (N c ,K c ) corresponding to The smallest median The corresponding value (N c ,K c ) as the first information length and the first code length, that is, the first information length and the first code length are candidates (N c ,K c ) is the one with the best AUB performance. It should be understood that the performance of AUB is based on the parameters The value of The smaller the value of is, the better the performance of AUB is.

[0138] Based on the above scheme, this application determines the parameters according to the performance criteria of AUB. The first information length and first code length corresponding to the value of are used for partial convolutional coding in MPAC codes. Determining these first information lengths improves the design of MPAC-like codes. Given the code length N and information length K, MPAC coding schemes with superior AUB performance can be identified, enriching the theory of MPAC code construction. Furthermore, directly using AUB performance (also known as asymptotic ML performance) as a design criterion better meets the requirements of future communication systems for higher reliability channel coding schemes.

[0139] From the above, we can see that the parameters The size is affected by d min and The influence of d min and The size of the candidate parameter (N c ,K c ), that is, the influence of different (N c ,K c ) calculated d min and Different. Considering the candidate parameters (N c ,K c ) has a total of (N-K+1)×K combinations, which is approximately in square relationship with the information length. Therefore, this application uses a calculation method for the MWD of MPAC codes based on cosets, which can calculate d with lower complexity. min and For any candidate (N c ,K c ), the MWD calculation method of MPAC code based on coset is used to calculate the (N c ,K c ) corresponding to d min and Provide detailed explanation.

[0140] Step 1, Figure 9 is a schematic diagram of the channel selection scheme of the MPAC code. As shown in Figure 9, for the candidate (N c ,K c ) in any one (N c ,K c ), determine the set according to the MPAC code rate configuration I and code rate configuration II in, K is determined according to the bit rate configuration I c The set of polarization sub-channel subscripts where the information bits are located, that is, the sub-information vector The polarization channel subscript set where is the polarization sub-channel index set where the information bit that directly performs polarization transformation (or does not perform convolution transformation) is located, that is, another sub-information vector The polarization channel subscript set where N c -K c The polarization sub-channel index set where the frozen bits entering the convolution transform are located, that is, the carrier vector Divisor information vector The subscript set of polarization channels other than the polarization channel where , so Represents NN c -K+K c The polarization sub-channel index set where the frozen bits that directly undergo polarization transformation (or do not undergo convolution transformation) are located, that is, the carrier vector Medium The polarization channel subscript and The set of polarization channel subscripts other than the polarization channel subscript where These are examples of the first set, the second set, the third set, and the fourth set respectively. Bitrate configuration I uses the iRMP criterion, and bitrate configuration II uses the GA criterion.

[0141] It should be noted that MPAC codes are similar to Polar codes. MPAC coding encodes an information bit sequence of length K into a bit sequence of length N. These N bits correspond to N polarization subchannels, so the subscript set of the polarization subchannels is [1, N]. Since the subscript index value starts counting from 0, the index set corresponding to the polarization subchannel subscripts is [0, N-1].

[0142] Step 2: According to the collection Determine d min and

[0143] Specifically, for this one (N c ,K c )The minimum Hamming distance ω of the MPAC code constructed min and the polar transformation matrix G of the MPAC code p Line g i The Hamming weight of G p Line g i The smallest Hamming weight among them, It is expressed as Among them, w(g i ) is G p Line g i The Hamming weight of .

[0144] It should be noted that the ω here min That is a (N c ,K c ) The minimum Hamming weight d of the constructed MPAC code min , so

[0145] In order to measure the (N c ,K c ) constructs the AUB performance of the MPAC code, and the AUB performance is related to the parameters The value of , and The value of the minimum Hamming weight d min and the number of MWC So the minimum Hamming weight is ω minOn the basis of this, it is also necessary to calculate the Hamming weight of the MPAC code as ω min The number of code words

[0146] Specifically, define the polar transformation matrix G p The coset of the i-th row of is Should It is expressed as follows:

[0147] in, Indicates that The subscript i in G corresponds to p The i-th row g i XOR The elements (or rows) in a collection, represents the exclusive OR operation, The rows included in the set are not included in the row [0,i] It should be understood that G p The i-th row of can also be regarded as the polarization subchannel subscript i of the MPAC code, where i is used to indicate the polarization subchannel position.

[0148] Therefore, the number of MWCs in the entire MPAC code is For each coset The sum of the number of MWCs is expressed as follows:

[0149] in, For coset The weight of the bank satisfies w(g i )=ω min The number of .

[0150] It should be noted that one row of the polarization transformation matrix corresponds to one codeword. It can be understood that the Hamming weight of a row of the polarization transformation matrix is ​​the row weight of the row. From the above-mentioned RM (Reed Muller) code construction method, it can be known that the polarization transformation matrix G p The row weight of each row, and each coset The number of rows whose weight is equal to the minimum Hamming weight is And because one line corresponds to one code word, that is Also for each coset The number of codewords whose Hamming weight is equal to the minimum Hamming weight.

[0151] From this we can see that we only need to know the number of MWCs that all cosets have The number of MWCs in the entire code is It can be obtained. Therefore, it is necessary to calculate the number of MWCs in a coset. Next, we calculate the number of MWCs in a coset The method is described in detail.

[0152] It should be noted that That is That is, one (N c ,K c ) is the number of codewords with the minimum Hamming weight in the MPAC code constructed.

[0153] This application is based on the MWC of the i-th coset in the Polar code, which is generated by the generator matrix G p The linear combination of the rows of , we get the linear combination of the MWC of the i-th coset in the MPAC code, as follows:

[0154] The coset leader i needs to satisfy w(g i )=ω min and Figure 10 is a Wayne diagram of the sets involved in the coset of the first i on [i+1, N-1]. The meaning of and constructing a set on element i Detailed description of the process

[0155] As shown in Figure 10, the set For collection A subset of gather It can be constructed using the following formula, namely

[0156] in, The operation represents the support set of the binary expression of i, that is, bin(i) = i n-1 ...i1i0 and The bin function represents the decimal to binary conversion, and i0 represents the first element from right to left after the binary conversion. For example, when i = 11, bin(i) = bin(11) = i3i2i1i0 = 1011, so i3 = 1, i2 = 0, i1 = 1, i0 = 1.

[0157] Therefore, the set The elements in can be generated in the binary basis of i in the following two ways.

[0158] The first is the left shift operation, which swaps the low-order '1' and high-order '0' of the binary value of i. And a<b.

[0159] For example, if i=11, the binary value of i is 1011. By swapping the low-order '1' and the high-order '0', we get 1101. The decimal value of the binary 1101 is 13. Therefore, based on i=11, the set generated by the first method is The elements in can include 13. In addition, the low bit '1' and the high bit '0' of 1101 can also be swapped to get 1110, then the decimal 14 corresponding to 1110 can also be included in the set middle.

[0160] The second is the addition operation, which changes any '0' in the binary value of i to '1', that is, The set can be calculated by the following formula The number of elements in

[0161] in, And gather For collection A subset of

[0162] For example, if i=11, the binary value of i is 1011. By changing any '0' in the binary value of i to '1', we can get 1111. The decimal value of binary 1111 is 15. Therefore, based on i=11, the set generated by the second method is The elements in can include 15.

[0163] It can be understood that the row weight of the pole transformation matrix corresponding to i is the smallest, and the calculation formula of the row weight can be known from the above as ω(g i )=2 b(i) , b(i) is the number of 1s in the binary representation of i, and the iRMP criterion is to get the set from large to small according to the row weight and collection Therefore, the set The elements in are greater than i and less than N-1 and the row weight is greater than or equal to the minimum row weight ω(g i ), so the set The number of 1s in the binary representation of each element in is greater than or equal to the number of 1s in the binary representation of i.

[0164] gather Corresponding to the frozen bit position of the input convolution transform, it can be seen from Figure 10 that The frozen bit position in the code rate configuration of Polar code is fixed to u f=0 is different from the fact that these frozen bit positions also have a constraint relationship with the previous input bits due to the convolution transformation, which may cause u f = 1. Therefore, the definition causes u f =1 is the set of bit positions The set satisfies the following formula:

[0165] As can be seen from Figure 10, the set Satisfy the set relationship

[0166] The set in Figure 10 Using MWC composition theory similar to Polar code Table 2 shows the algorithm #2 implementation added to Position-by-position element construction in a collection The process diagram of the collection is as follows:

[0167] Table 2 Schematic diagram of the construction process of a set

[0168] As shown in Table 2, in the process set The newly added element j and Then let u j =1, the set Equivalent to belonging to the set Any element j of But there is u j = 1. The process sets constructed in the process of adding new elements are defined as and During the step-by-step construction, element j needs to be and Each element in the set constitutes A set consisting of two elements j and e and For each The collection is judged, when When it is established, the construction element m ε satisfy Considering m ε and The relationship between the sets, if but like but In all After traversing, By increasing the index position j one by one until the set After all the elements j in are traversed, the set is finally obtained. This enables the collection Corresponding to a unique set Satisfy the set relationship

[0169] Since this application follows the linear combination theory of MWC of polar code, the set The row in the polar transformation matrix corresponding to the elements in is called the "key row", that is, the key row g j satisfy And will be The set obtained by the construction algorithm The corresponding row is called the "balancing row", that is, the balancing row g m satisfy The row g corresponding to the key row and the balance row and the coset leader i i The common linear combination can form an MWC codeword, and the set of subscripts of these rows can be defined as and satisfy It is shown in the dotted box in Figure 6. It can be understood that a codeword is composed of the key row and the balance row and the row g corresponding to the coset leader i. i Common linear combination, so the number of subscript sets obtained by all possible linear combinations represents the number of MWC codewords. A unique set can be constructed Therefore, the number of MWCs is equal to the number of all possible sets And because And gather Generation and collection of Therefore, without considering the actual coding constraints, the number of MWCs is equal to all sets The number of

[0170] It should be noted that since a MWC codeword is based on the key row and the balance row and the g corresponding to the coset first i i The number of MWCs is equal to The number of linear combinations of the elements in , that is times. For example, when When includes 3 elements, the number of MWCs is 8.

[0171] In addition, the calculation of the number of MWCs also includes an important condition, namely the subscript set The row g corresponding to any subscript element x in x can be included in the actual encoding process of MPAC code to form MWC, and the meaning of being included is for Then u x = 1. Therefore, when MPAC code can form MWC, the following conditions are met, namely

[0172] It can be understood that for each MWC that can be constructed, the row set corresponding to the MWC is Determined position by position during the MPAC code encoding process Should satisfy in express If the row set corresponding to a MWC If the above conditions are not met, the MWC cannot be formed and the final number of MWCs will be reduced. The following section will explain in detail how to calculate the actual number of MWCs.

[0173] Table 3 shows a coset of MPAC code calculated by Algorithm #3 Number of MWCs The process diagram is as follows:

[0174] Table 3 Calculation of the number of MWCs of a coset of MPAC codes Process diagram

[0175] As shown in Table 3, the number of MWCs finally calculated can be expressed as Among them, X represents not meeting The number of MWCs that cannot be formed due to the conditions. The calculation formula shows that as long as the value of X is obtained, The shaded part in Figure 10 shows the set relationship that can cause the value of X to change. If an element belongs to the shaded set, it is considered that the current set consists of the coset head i and the set If the determined MWC cannot be constructed, X will be incremented by 1. At the beginning of the calculation, the set and collection in, Satisfies the following formula, namely

[0176] According to the set relationship and definition, if This means that there must be no element belonging to the shadow set, so X = 0, and we can directly get This is reflected in rows 1 to 3 of Table 3.

[0177] The above is the case where no element belongs to the shadow set. That is to say, if there are subscript elements belonging to the shadow set, it is necessary to Each MWC is judged separately to calculate X. For each MWC judgment process, the bit position u i+1 Determine the bit position u position by position N-1 . Assume that the current traversed position is u z , then u z The value of is determined in two cases: the first case is determined by the set membership relationship; the second case is determined by the convolution constraint or frozen bits. The second case may cause changes in X.

[0178] The first case mainly targets the location That is, the polarization channel position where the information vector is located. Here, z can be understood as the polarization channel subscript index. Then set u z = 1 and construct the set according to the update process in Table 2 and In Table 3, it is shown in row 11; if Then set u z =1; otherwise, set u z = 0. In particular, when the position satisfies When u z The value is generated by the convolution transformation and is represented as u z =v k and In this process, the changes of the shift register need to be recorded, so we will look for the conditions that make v k =u z The input bits s that hold k , and s k Single-bit convolution encoding is performed according to the method in Table 1 to update the state S of the shift register, which is reflected in rows 14 and 16 to 18 in Table 3.

[0179] The second case mainly targets the location or like Then u z =v k , and [v k ,S]←conv1b(sk ,S,g0 t ),u z The value will be determined by the constraints of the convolution bits, then s k = 0. If Then u z = 0 is determined by the value of the frozen bit. The subordination of the set and u z The value of is used to determine whether z belongs to the shadow set as follows:

[0180] a. belong to Collection but not part of Collection and does not belong to The left oblique shadow part of the set, so according to the set relationship, we need to judge and It is expressed as andu z =1, as shown in row 22 of Table 3;

[0181] b. belongs to Collection but not part of The vertical line shaded part of the set, so the set relationship can be converted into a judgment and It is expressed as andu z =0, as shown in row 23 of Table 3;

[0182] c. belongs to Collection and belongs to The right-slashed shaded portion of the set: u z =0, Therefore, the set relation can be converted into a judgment and It is expressed as andu z =0, as shown in row 27 of Table 3

[0183] Whenever an element z satisfies one of the above three conditions, it is considered that the current one consists of the coset leader i and the set If the determined MWC cannot be constructed, X is incremented by 1, and the traversal of the current MWC can be skipped.

[0184] Until all Each MWC is judged whether it can be formed, and each time it is judged from bit u i+1 Start to determine bit u one by one N-1 , a total of N-1-i bit positions, if MWCs can be constructed, then the number of MWCs in the final MPAC codeword is It can be seen that its computational complexity is approximately

[0185] Based on the above solution, this application proposes a method for calculating the number of MWCs in an MPAC code based on coset angles. Compared to the MWD calculation method implemented by simulation, this method has lower computational complexity. Therefore, it can be more effectively applied to calculate the AUB performance of different MPAC codes, that is, to evaluate the asymptotic ML performance of the code.

[0186] So far, for multiple candidate convolutions (N c ,K c ) in each (N c ,K c ), each (N c ,K c ) corresponding to d min and Thus, each (N c ,K c ) corresponds to the upper limit of AUB From multiple According to the first condition, determine a Corresponding (N c ,K c ), that is, the first information length and the first code length, the finally determined first information length and the first code length are used to construct the MPAC code.

[0187] S730. The transmitting end device performs MPAC encoding on the information bit sequence according to the first parameter group to obtain a first MPAC codeword sequence.

[0188] Specifically, the transmitting device performs MPAC encoding on the information bit sequence according to the first information length and the first code length to obtain a first MPAC codeword sequence, wherein the first information length and the first code length are an example of the first value and the second value in the first parameter group.

[0189] Specifically, the coding structure of the MPAC code needs to determine the convolution parameters (N c ,K c ), according to S720, the appropriate parameter (N c ,K c ), that is, the first information length and the first code length are used for MPAC encoding. The transmitting end device can encode the information bit sequence according to the MPAC encoding structure determined by the first information length and the first code length to obtain a first MPAC codeword sequence.

[0190] S740. The transmitting device sends a first MPAC codeword sequence and first indication information. Correspondingly, the receiving device receives the first MPAC codeword sequence and first indication information from the transmitting device, where the first indication information is used to indicate a first parameter group.

[0191] That is, the transmitting device sends the first MPAC codeword sequence, the first information length and the first code length to the receiving device, and accordingly, the receiving device receives the first MPAC codeword sequence, the first information length and the first code length from the transmitting device.

[0192] It should be noted that, when the transmitting end device determines the first information length and the first code length, the first information length and the first code length of the receiving end may also be predefined by the protocol.

[0193] S750. The receiving device performs MPAC decoding on the first MPAC codeword sequence according to the first parameter group.

[0194] That is, the receiving device performs MPAC decoding on the first MPAC codeword sequence according to the first information length and the first code length.

[0195] It should be noted that, since the first MPAC codeword sequence may introduce channel noise signals during the transmission process, the first MPAC codeword sequence output or sent by the transmitting device may be different from the first MPAC codeword sequence received by the receiving device.

[0196] The performance of the MPAC code of the embodiment of the present application is described below in conjunction with simulation results.

[0197] Given the code length N and information dimension K of the MPAC code, this application obtains different convolution parameters (N c ,K c ) and simulate the FER and normalized complexity performance of different MPAC codes under HFSC decoding under AWGN channel and BPSK modulation. For example, the convolution transform generator polynomial used by MPAC code is g(x)=1+x 2 +x 2 +x 2 +x 6 , bit rate configuration II adopts GA criterion, and SNR is taken as E s / N0=0.0dB is used to measure reliability. When optimizing, the iRMP criterion is preferred for bit rate configuration I. Figures 11 and 13 show the different AUB performance evaluations (N c ,K c ) The result graph of the MAPC code constructed by . The evaluation criteria of AUB is The smaller the value, the better the AUB performance of the MPAC code.

[0198] Figure 11 shows the MPAC code with (N, K) = (128, 64) at different (N c ,K c ) under AUB performance. The pure black plane represents the AUB performance of the PAC code constructed by RM, and the MWD of the PAC code is ω min =16, A 16 =3120, and this value is used as the benchmark for performance comparison. As can be seen from Figure 11, under this benchmark, there are many (N c ,K c ) parameter selection scheme can obtain better AUB performance than PAC, that is, below the pure black plane (N c ,K c ) constructed MPAC code has better AUB performance, or better progressive ML performance. The optimal AUB solution obtained by this application based on simulation results (N c ,K c ) parameter is (65 , 45) * , the (65 , 45) * The corresponding MWD of the MPAC code is ω min =16, A 16 =2633. In addition, the present application also calculates the MWD of CRC-Polar code by simulation method as ω min =12, A2=224.

[0199] Figure 12 shows the performance comparison of FER and normalized complexity of different encoding and decoding schemes with (N, K) = (128, 64). According to the simulation results of Figure 11, the best AUB performance is obtained for (N c ,K c ) parameter is (65 , 45) * Figure 12 shows the simulation results of the optimized parameters (65 , 45) * The performance advantage of the constructed MPAC code under HFSC decoding is that the path metric value of the MPAC code is s The calculation is performed under / N0=1.5dB, and the decoding step size is Δ=2. Figure 12 sets the parameters to (65,45) *The MPAC code of this application is compared with the PAC code and the CRC-Polar code. The PAC code used in this comparison is a PAC code that adopts RM construction and uses the same convolution transform generating polynomial g(x) as the MPAC code. The Fano decoding parameters used by the PAC code are the same as the HFSC decoding configuration used by the MPAC code. In addition, the MPAC code of this application and the compared PAC code will adopt the decoding complexity upper limit η to simulate the complexity limitation in actual application. The compared CRC-Polar code is constructed using a 5G NR reliable sequence, where the generating polynomial of CRC is p(x)=1+x+x 2 +x 8 , the decoding method adopts the Successive Cancellation List (SCL) algorithm. As shown in Figure 12, compared with PAC code and CRC-Polar code, under high SNR conditions, the optimized parameters are (65,45) * The MPAC code scheme can achieve a win-win advantage in decoding performance and decoding complexity. In addition, compared with other MPAC (N c ,K c ) parameter constructed MPAC code scheme, the optimized (N c ,K c ) parameter is (65 , 45) * The MPAC code can achieve better FER performance with similar complexity under high SNR conditions, which reflects the effectiveness of the design based on AUB performance and the advantage of its progressive ML performance.

[0200] Figure 13 shows the MPAC code with (N, K) = (256, 163) using different parameters (N c ,K c The pure black plane represents the AUB performance of the PAC code constructed by RM, and the MWD of the PAC code is ω min =16, A 16 =18896, and this value is used as the benchmark for performance comparison. As can be seen from Figure 13, under this benchmark, there are many (N c ,K c ) parameter selection scheme can obtain better AUB performance than PAC, that is, the parameter (N c ,K c ) constructed MPAC code has better AUB performance, or better progressive ML performance. The optimal AUB solution obtained by this application based on simulation results (N c ,K c ) parameter is (169 , 132) *, the (169 , 132) * The corresponding MWD of the MPAC code is ω min =16, A 16 =15622. In addition, the present application also calculates the MWD of CRC-Polar code by simulation method as ω min =8, A8=4.

[0201] Figure 14 shows the performance comparison of FER and normalized complexity of different encoding and decoding schemes with (N, K) = (256, 163). According to the simulation results of Figure 13, the best AUB performance is obtained for (N c ,K c ) parameter is (169 , 132) * Compared with CRC-Polar code scheme, PAC code scheme and other (N c ,K c ) parameter MPAC code scheme, after optimization design (N c ,K c ) parameter is (169 , 132) * The constructed MPAC code can achieve asymptotically better FER performance and also demonstrate the advantages of its asymptotic ML performance.

[0202] The above describes in detail the method embodiment provided by the present application in conjunction with Figures 1 to 14 , and the following will describe the device embodiment of the present application in conjunction with Figures 15 to 17 .

[0203] In order to realize the various functions of the communication devices (such as network devices, terminal devices) in the embodiments of the present application, each communication device can realize the corresponding functions through hardware structure, software module, or hardware structure plus software module.

[0204] Figure 15 is a schematic block diagram of a communication device 1000 provided in an embodiment of the present application. As shown in Figure 15, the device 1000 may include a transceiver unit 1010 and a processing unit 1020. The transceiver unit 1010 can communicate with the outside world, and the processing unit 1020 is used for data processing. The transceiver unit 1010 may also be referred to as a communication interface or a transceiver unit.

[0205] Optionally, the device 1000 may further include a storage unit, which may be used to store instructions and / or data. The processing unit 1020 may read the instructions and / or data in the storage unit so that the device implements the aforementioned method embodiment.

[0206] Exemplarily, the communication device 1000 can be the sending end device (terminal device or network device) in the above method, or it can be a communication device applied to the sending end device or used in combination with the sending end device and capable of implementing the method executed by the sending end device, such as a chip, chip system or circuit. For details, please refer to the relevant description of the chip system shown in Figure 17.

[0207] Exemplarily, the communication device 1000 can be the receiving device (terminal device or network device) in the above method, or it can be a communication device applied to the receiving device or used in combination with the receiving device and capable of implementing the method executed by the receiving device, such as a chip, chip system or circuit. For details, please refer to the relevant description of the chip system shown in Figure 17.

[0208] In one possible design, the device 1000 can implement steps or processes corresponding to those performed by the sending end device in the above method embodiment, wherein the processing unit 1020 is used to perform processing-related operations of the sending end device in the above method embodiment, and the transceiver unit 1010 is used to perform transceiver-related operations of the sending end device in the above method embodiment.

[0209] Exemplarily, the transceiver unit 1010 is configured to transmit a first MPAC codeword sequence and a first parameter group. The processing unit 1020 is configured to determine the first parameter group from a plurality of parameter groups, or the processing unit 1020 is configured to perform MPAC encoding on the information bit sequence according to the first parameter group to obtain the first MPAC codeword sequence.

[0210] In another possible design, the device 1000 can implement steps or processes corresponding to those performed by the receiving device in the above method embodiment, wherein the transceiver unit 1010 is used to perform the transceiver-related operations of the receiving device in the above method embodiment, and the processing unit 1020 is used to perform the processing-related operations of the receiving device in the above method embodiment.

[0211] Exemplarily, the transceiver unit 1010 is configured to receive a first MPAC codeword sequence and a first parameter group, and the processing unit 1020 is configured to decode the first MPAC codeword sequence according to the first parameter group.

[0212] It should be understood that the device 1000 here is embodied in the form of a functional unit. The term "unit" here may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a dedicated processor or a group processor, etc.) and a memory for executing one or more software or firmware programs, a merging logic circuit and / or other suitable components that support the described functions. In an optional example, those skilled in the art will understand that the device 1000 can be specifically the transmitting end in the above-mentioned embodiment, and can be used to execute the various processes and / or steps corresponding to the transmitting end in the above-mentioned method embodiment, or the device 1000 can be specifically the receiving end in the above-mentioned embodiment, and can be used to execute the various processes and / or steps corresponding to the receiving end in the above-mentioned method embodiment. To avoid repetition, it will not be described here.

[0213] The device 1000 of each of the above-mentioned solutions has the function of implementing the corresponding steps performed by the sending end in the above-mentioned method, or the device 1000 of each of the above-mentioned solutions has the function of implementing the corresponding steps performed by the receiving end in the above-mentioned method. The functions can be implemented by hardware, or the corresponding software can be implemented by hardware. The hardware or software includes one or more modules corresponding to the above-mentioned functions; for example, the transceiver unit can be replaced by a transceiver (for example, the sending unit in the transceiver unit can be replaced by a transmitter, and the receiving unit in the transceiver unit can be replaced by a receiver), and other units, such as the processing unit, can be replaced by a processor to respectively perform the transceiver operations and related processing operations in each method embodiment.

[0214] In addition, the above-mentioned transceiver unit can also be a transceiver circuit (for example, it can include a receiving circuit and a transmitting circuit), and the processing unit can be a processing circuit. In an embodiment of the present application, the above-mentioned communication device can be the receiving end or the transmitting end in the aforementioned embodiment, or it can be a chip or a chip system, such as a system on chip (SoC). Among them, the transceiver unit can be an input and output circuit or a communication interface. The processing unit is a processor or microprocessor or integrated circuit integrated on the chip. This is not limited here.

[0215] Figure 16 is a schematic block diagram of a communication device 2000 provided in an embodiment of the present application. As shown in Figure 16, the device 2000 includes a processor 2010 and a transceiver 2020. The processor 2010 and the transceiver 2020 communicate with each other via an internal connection path. The processor 2010 is configured to execute instructions to control the transceiver 2020 to transmit and / or receive signals.

[0216] Optionally, the apparatus 2000 may further include a memory 2030, which communicates with the processor 2010 and the transceiver 2020 via an internal connection path. The memory 2030 is used to store instructions, and the processor 2010 may execute the instructions stored in the memory 2030.

[0217] Exemplarily, the communication device 2000 is a transmitting device, or it can be a communication device applied to a transmitting device or used in combination with a transmitting device and capable of implementing the method executed by the transmitting device, such as a chip, a chip system or a circuit. For details, please refer to the relevant description of the chip system shown in Figure 17.

[0218] Exemplarily, the communication device 2000 is a receiving device, or it can be a communication device applied to a receiving device or used in combination with a receiving device and capable of implementing a method executed by the receiving device, such as a chip, a chip system or a circuit. For details, please refer to the relevant description of the chip system shown in Figure 17.

[0219] In a possible implementation, the apparatus 2000 is used to implement various processes and steps corresponding to the transmitting end device in the above method embodiment.

[0220] In another possible implementation, the apparatus 2000 is used to implement the various processes and steps corresponding to the receiving device in the above method embodiment.

[0221] Optionally, the memory 2030 may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information. The processor 2010 may be configured to execute instructions stored in the memory. When the processor 2010 executes the instructions stored in the memory, the processor 2010 is configured to perform the various steps and / or processes of the above-described method embodiments corresponding to the transmitting end or the receiving end.

[0222] During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it will not be described in detail here.

[0223] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above-described method embodiments can be completed by hardware integrated logic circuits in the processor or by software instructions. The above-described processor can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or the aforementioned CPU, other general-purpose processors, a DSP, an ASIC, an FPGA or other programmable logic device, or a portion of the circuitry in other chips used for processing functions. The processor in the embodiments of the present application can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in a memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above-described method.

[0224] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0225] In the embodiments of the present application, the above-described method may be executed by a transmitting device or a receiving device, or may be executed by a chip, chip system, or circuit of the transmitting device or the receiving device. The chip, chip system, or circuit may be installed in the transmitting device or the receiving device. The chip system of the transmitting device or the receiving device is described below with reference to FIG17.

[0226] FIG17 is a schematic block diagram of a chip system 3000 according to an embodiment of the present application. As shown in FIG17 , the chip system 3000 (or also referred to as a processing system) includes a logic circuit 3010 and an input / output interface 3020 .

[0227] Logic circuit 3010 may be a processing circuit in chip system 3000. Logic circuit 3010 may be coupled to a storage unit and call instructions in the storage unit, so that chip system 3000 can implement the methods and functions of various embodiments of the present application. Input / output interface 3020 may be an input / output circuit in chip system 3000, outputting information processed by chip system 3000 or inputting data or signaling information to be processed into chip system 3000 for processing.

[0228] As a solution, the chip system 3000 is used to implement the operations performed by the transmitting device or the receiving device in each of the above method embodiments.

[0229] For example, the logic circuit 3010 is used to implement the processing-related operations performed by the sending end device in the above method embodiments, such as the processing-related operations performed by the sending end device in the above embodiment; the input / output interface 3020 is used to implement the sending and / or receiving-related operations performed by the sending end device in the above method embodiments, such as the sending and / or receiving-related operations performed by the sending end device in the above embodiment.

[0230] For another example, the logic circuit 3010 is used to implement the processing-related operations performed by the receiving device in the above method embodiments, such as the processing-related operations performed by the receiving device in the above embodiments; the input / output interface 3020 is used to implement the sending and / or receiving-related operations performed by the receiving device in the above method embodiments, such as the sending and / or receiving-related operations of the receiving device in the above embodiments.

[0231] An embodiment of the present application further provides a computer-readable storage medium on which computer instructions for implementing the methods executed by a transmitting device or a receiving device in the above-mentioned method embodiments are stored.

[0232] An embodiment of the present application also provides a computer program product, comprising instructions, which, when executed by a computer, implement the methods performed by a sending device or a receiving device in the above-mentioned method embodiments.

[0233] An embodiment of the present application further provides a communication system, which includes the transmitting device or the receiving device in the above embodiments.

[0234] The explanation of the relevant contents and beneficial effects of any of the above-mentioned devices can be referred to the corresponding method embodiments provided above, which will not be repeated here.

[0235] In this application, under the premise of no logical contradiction, the examples can reference each other, for example, the methods and / or terms between method embodiments can reference each other, for example, the functions and / or terms between device embodiments can reference each other, for example, the functions and / or terms between device examples and method examples can reference each other.

[0236] In various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0237] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0238] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0239] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0240] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0241] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0242] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0243] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A communication method based on an improved polarization-adjusted convolutional code, characterized in that: include: Obtaining a first sequence to be encoded, where the first sequence includes K information bits, where K ≥ 1; A first parameter group is determined from a plurality of parameter groups, each parameter group including a first value K c and the second value N c , the first value K c is a candidate value of the number of information bits included in the first subsequence that needs to be convolutionally transformed among the K information bits, and the second value N c is a candidate value of the number of bits included in the second sequence obtained after the first subsequence is convolutionally transformed, 1≤K c ≤K,N c ≥1, K c ≤N c ; Performing improved polarization-adjusted convolutional code (MPAC) encoding on the first sequence according to the first parameter group to obtain a first MPAC codeword sequence; The first MPAC codeword sequence and first indication information are sent, where the first indication information is used to indicate the first parameter group.

2. The method according to claim 1, characterized in that Each parameter group in the plurality of parameter groups corresponds to an MPAC code, and the upper bound value of the approximate joint bound of the MPAC code corresponding to the first parameter group is The following conditions are met: The first parameter group corresponds to is less than or equal to a preset first threshold; or, The first parameter group corresponds to The multiple parameter groups corresponding to The one with the smallest median value; described is determined according to the minimum Hamming weight in the MPAC code corresponding to each parameter group and the number of codewords with the minimum Hamming weight, Among them, the satisfy d min is the minimum Hamming weight of the MPAC code corresponding to each parameter group, The Hamming weight of the MPAC code corresponding to each parameter group is d min The number of code words, Q (·) is the complement function of the Gaussian cumulative distribution function, R is the code rate of the first MPAC code word sequence, R = K / N, N is the code length of the first MPAC code word sequence, the E b is the signal power per bit, N0 is the noise power spectral density, E b / N0→∞.

3. The method according to claim 2, characterized in that The d min satisfy Among them, w(g i ) is the Hamming weight of the i-th row in the first polarization transformation matrix corresponding to the first MPAC codeword sequence, For the first set, is a second set, where the first set is a set of polarization subchannel subscripts for information bits included in the first subsequence, and the second set is a set of polarization subchannel subscripts for information bits included in a second subsequence that directly performs polarization transformation among the K information bits. described for Yukiwa, stated The Hamming weight in the coset of the i-th row of the first polarization transformation matrix is ​​d min The number of code words.

4. The method according to claim 3, characterized in that described The method is determined based on i, the first set, the second set, the third set, the fourth set, and the convolution transformation vector corresponding to each parameter group, wherein the third set is a set of polarization subchannel indexes for frozen bits in the second sequence excluding information bits included in the first subsequence, and the fourth set is a set of polarization subchannel indexes for frozen bits in the first MPAC codeword sequence excluding bits included in the second sequence and information bits included in the second subsequence.

5. The method according to claim 4, characterized in that The first set, the second set, the third set and the fourth set corresponding to each parameter group are determined according to the code rate configuration I and the code rate configuration II, the code rate configuration I uses the adjusted RM-Polar criterion, and the code rate configuration II uses the Gaussian GA criterion.

6. A communication method based on an improved polarization-adjusted convolutional code, characterized in that: include: receiving a first MPAC codeword sequence and first indication information, where the first indication information is used to indicate a first parameter group; Performing MPAC decoding on the first MPAC codeword sequence according to the first parameter group; The first MPAC codeword sequence is obtained by performing MPAC encoding on a first sequence to be encoded according to the first parameter group, the first sequence including K information bits, where K≥1; The first parameter group is determined from a plurality of parameter groups, wherein each parameter group includes a first value K c and the second value N c , the first value K c is a candidate value of the number of information bits included in the first subsequence that needs to be convolutionally transformed among the K information bits, and the second value N c is a candidate value of the number of bits included in the second sequence obtained after the first subsequence is convolutionally transformed, 1≤K c ≤K,N c ≥1, K c ≤N c .

7. The method according to claim 6, characterized in that Each parameter group in the plurality of parameter groups corresponds to an MPAC code, and the upper bound value of the approximate joint bound of the MPAC code corresponding to the first parameter group is The following conditions are met: The first parameter group corresponds to is less than or equal to a preset first threshold; or, The first parameter group corresponds to The multiple parameter groups corresponding to The one with the smallest median value; described is determined according to the minimum Hamming weight in the MPAC code corresponding to each parameter group and the number of codewords with the minimum Hamming weight, Among them, the satisfy d min is the minimum Hamming weight of the MPAC code corresponding to each parameter group, The Hamming weight of the MPAC code corresponding to each parameter group is d min The number of code words, Q (·) is the complement function of the Gaussian cumulative distribution function, R is the code rate of the first MPAC code word sequence, R = K / N, N is the code length of the first MPAC code word sequence, the E b is the signal power per bit, N0 is the noise power spectral density, E b / N0→∞.

8. The method according to claim 7, characterized in that The d min satisfy Among them, w(g i ) is the Hamming weight of the i-th row in the first polarization transformation matrix corresponding to the first MPAC codeword sequence, For the first set, is a second set, where the first set is a set of polarization subchannel subscripts for information bits included in the first subsequence, and the second set is a set of polarization subchannel subscripts for information bits included in a second subsequence that directly performs polarization transformation among the K information bits. described for Yukiwa, stated The Hamming weight in the coset of the i-th row of the first polarization transformation matrix is ​​d min The number of code words.

9. The method according to claim 8, characterized in that described The method is determined based on i, the first set, the second set, the third set, the fourth set, and the convolution transformation vector corresponding to each parameter group, wherein the third set is a set of polarization subchannel indexes for frozen bits in the second sequence excluding information bits included in the first subsequence, and the fourth set is a set of polarization subchannel indexes for frozen bits in the first MPAC codeword sequence excluding bits included in the second sequence and information bits included in the second subsequence.

10. The method according to claim 9, characterized in that The first set, the second set, the third set and the fourth set corresponding to each parameter group are determined according to the code rate configuration I and the code rate configuration II, the code rate configuration I uses the adjusted RM-Polar criterion, and the code rate configuration II uses the Gaussian GA criterion.

11. A communication device, characterized in that: The apparatus comprises a unit or module for executing the method according to any one of claims 1 to 5 , or the apparatus comprises a unit or module for executing the method according to any one of claims 6 to 10 .

12. A communication system, characterized in that: include: A sending end device and a receiving end device, wherein the sending end device is used to execute the method according to any one of claims 1 to 5, and the receiving end device is used to execute the method according to any one of claims 6 to 10.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions. When the computer program runs on a computer, the computer is caused to execute the method according to any one of claims 1 to 5, or the computer is caused to execute the method according to any one of claims 6 to 10.

14. A computer program product, characterized in that The computer program product comprises: a computer program code, which, when running on a communication device, causes the device to perform the method according to any one of claims 1 to 5, or causes the device to perform the method according to any one of claims 6 to 10.

15. A chip system, characterized in that: include: A processor for calling and running a computer program from a memory so that a communication device equipped with the chip system executes a method as described in any one of claims 1 to 5, or a communication device equipped with the chip system executes a method as described in any one of claims 6 to 10.

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