Data processing method, device, equipment, and storage medium

Abstract

The present application discloses a data processing method, an apparatus, a device, and a storage medium, which includes mapping information bits in the information bit sequence to information and frozen bit sequences according to a Gray mapping rule, and then encoding the information and frozen bit sequences to obtain the encoded data sequence.

Description

[Technical Field]

[0001] This application is filed based on a Chinese patent application bearing application number 202211557600.9 and filed on December 6, 2022, and claims priority to that Chinese patent application, the entire contents of which are incorporated herein by reference.

[0002] The present application relates to the field of communications, and in particular to data processing methods, devices, equipment, and storage media. [Background technology]

[0003] Polar codes are short codes with higher reliability, and therefore, in the 5th Generation Mobile Communication (5G) standard established by the 3rd Generation Partnership Project (3GPP (registered trademark)), polar codes are adopted as the coding scheme for 5GNR control information. Specifically, polar codes are adopted as the coding scheme for downlink control information (DCI), uplink control information (UCI), and broadcast information carried by the physical broadcast channel (PBCH) in the control channel.

[0004] Polar code sequences are used to indicate the bit selection order before encoding the polar code, i.e., "good channel selection." To support the flexible code length and code rate requirements of 5G NR control information, it is necessary to design a sufficiently practical subchannel reliability sorting sequence for polar codes. Polar weight (PW) sequences have been shown through standardization and practical application to have characteristics that are independent of channel parameters, and PW sequences can exhibit good and stable performance under various code length and code rate configurations.

[0005] In a specific application, the PW sequence can be obtained by calculating the polarization weights, sorting them in ascending order, and finding the sequence numbers of the input bits that correspond to them. Calculating the PW sequence in real time requires high precision when calculating the polarization weights, which requires many memory transistors. To obtain the PW sequence from the acquisition memory, a memory of size N is required. max A PW sequence of size N must be stored in memory. max The first N subsequences are extracted from the PW sequence to construct N subchannel reliability sorted sequences, where N is the number of N max This method reduces the overhead of online computing resources, but increases the overhead of storage. Summary of the Invention [Problem to be solved by the invention]

[0006] The present application provides a data processing method, apparatus, device, and storage medium for reducing the overhead of storage resources used in encoding Polar codes. [Means for solving the problem]

[0007] In a first aspect, the present embodiment comprises: obtaining an information bit sequence, the information bit sequence including K information bits, where K is an integer greater than 0; mapping information bits in the information bit sequence to information and frozen bit sequences according to a Gray mapping rule, wherein the information and frozen bit sequences include N bits, where N represents the number of polarization subchannels, and N is an integer greater than K; encoding the information and the frozen bit sequence to obtain the encoded data sequence; transmitting the encoded data sequence.

[0008] In a second aspect, the present embodiment comprises: receiving a coded data sequence transmitted by a transmitter, the coded data sequence including N coded data; The data processing method includes the steps of: mapping information bits in an information bit sequence to information and frozen bit sequences according to a Gray mapping rule; and encoding the information and frozen bit sequences to obtain the encoded data sequence; the information bit sequence includes K information bits, where K is an integer greater than 0; and the information and frozen bit sequences include N bits, where N represents the number of polarization subchannels, where N is an integer greater than K.

[0009] In a third aspect, the present embodiment comprises: at least one processor; at least one memory for storing at least one program; There is provided an electronic device that, when at least one of the programs is executed by at least one of the processors, realizes the data processing method according to the first or second aspect above.

[0010] In a fourth aspect, the present embodiment comprises: There is provided a computer-readable storage medium storing a processor-executable program that, when executed by a processor, realizes the data processing method according to the first or second aspect above.

[0011] In a fifth aspect, the present embodiment comprises: A computer program product is provided, the computer program product including a computer program or computer instructions, the computer program or the computer instructions being stored on a computer-readable storage medium, a processor of a computer device reading the computer program or the computer instructions from the computer-readable storage medium, and the processor executing the computer program or the computer instructions to cause the computer device to perform the data processing method according to the first or second aspect above. [Effects of the Invention]

[0012] In the embodiment of the present application, the information bits in the information bit sequence are mapped into information and frozen bit sequences according to a Gray mapping rule, and then the information and frozen bit sequences are coded to obtain the coded data sequence. By determining the sub-channel transmission information bits or frozen bits online using the Gray mapping method and then coding the information and frozen bit sequences, the storage overhead and the computational resources required to obtain the sub-channel reliability are reduced. [Brief explanation of the drawings]

[0013] [Figure 1a] FIG. 10 is a schematic diagram of logic code that realizes the addition of a frozen bit. [Figure 1b] FIG. 10 is a diagram showing polarization conversion coefficients for N=16. [Figure 2] 1 is a schematic diagram of the architecture of a communication system to which an embodiment of the present application is applied; [Figure 3] 1 is a flowchart of a data processing method according to an embodiment of the present application; [Figure 4] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 5] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 6] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 7] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 8] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 9] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 10] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 11] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 12] FIG. 1 is a schematic diagram of logic code for implementing updating of information and frozen bit sequences according to an embodiment of the present application; [Figure 13] FIG. 2 is a schematic diagram of a serially encoded logic code according to an embodiment of the present application; [Figure 14] FIG. 2 is a schematic diagram of a serially encoded logic code according to an embodiment of the present application; [Figure 15] 1 is a flowchart of another data processing method according to an embodiment of the present application. [Figure 16] 1 is a schematic diagram illustrating the configuration of a data processing device according to an embodiment of the present application. [Figure 17] 1 is a schematic diagram illustrating the configuration of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE INVENTION

[0014] The present application will now be further described with reference to the drawings and specific examples.

[0015] In the following description, "some embodiments" describes a subset of all possible embodiments, but "some embodiments" may be the same subset of all possible embodiments, or different subsets, and may be combined without contradicting each other.

[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art. The terms used herein are for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0017] In order to facilitate understanding of the solutions of the embodiments of the present application, the technical terms related to the embodiments of the present application will be explained below.

[0018] (1) Polar Weight (PW) sequence For a PW sequence, the formula for calculating the polarization subchannel reliability of index bit i is:

number

[0019] The number of polarization subchannels N max =2 n The quantization weight sequence β=[β n-1 ,β n-2 ,…,β0] is the number of polarization subchannels N=2 t It can be used for polar coding of (t=n, n-1, n-2, ..., 1). For example, n=10, N max For the quantization weight sequence β=[β9, β8, …, β0] calculated from =1024, the above configuration can be used for polar coding with polarization subchannel lengths N=1024, 512, 256, 128 …, so N can be set to 2 n For convenience of explanation, in the solution of the embodiment of the present application, N max Write all together in N, N=2 n To do so.

[0020] Table 1 shows a PW sequence for N=16, i.e., PW=[0,1,2,4,8,3,5,6,9,10,12,7,11,13,14,15], where the first element "0" represents the index number of the least reliable subchannel and the last element "15" represents the index number of the most reliable subchannel.

[0021] [Table 1] (2) Polar code encoding

[0022] a=[a0,a1,…,a K-1 ], a is an information sequence of length K, N is the number of polarization subchannels, and the information sequence a is a codeword d=[d0,d1,…,d N-1 ] is encoded as follows:

[0023] (1) Adding frozen bits: Select the appropriate subchannels to bear the information bits and the subchannels to place the frozen bits, and create an information sequence a = [a0, a1, ..., a K-1 ], add NK bits 0 to the sequence u = [u0,u1,…,u N-1 Illustratively, the process of adding the frozen bit can be realized by the logic code shown in FIG. 1a.

[0024]

number

[0025] In encoding a set of numbers, if any two adjacent codes differ by only one binary bit, the code is called a Gray code. There are various encoding formats for Gray code, and examples of typical Gray code are shown in Table 2.

[0026] [Table 2]

[0027] In this application, in Table 2, the natural decimal number i is converted to a typical Gray code decimal number g i The process of mapping the natural decimal number i-1 to the Gray code decimal number g i-1 is known, the Gray code decimal number g corresponding to the natural decimal number i i can be calculated by the following formula:

number

[0028] Similarly, the Gray code decimal number g corresponding to the natural decimal number i+1 is i+1 Similarly, if g is known, i+1 Based on the Gray code decimal number g corresponding to the natural decimal number i i can be calculated by the following formula:

number

[0029] In the 5G standard protocol TS38.212 established by 3GPP, the polar code sequence and the corresponding reliability are shown in a table. When the code length is N, a log2(N)*N-bit memory is required to store the polar code sequence. In the encoding process of encoding an information sequence a into a code word d of length N, first, the information sequence a=[a0,a1,...,a K-1 ], add NK bits 0 to the sequence u = [u0,u1,…,u N-1 ] is obtained. Next, the sequence u is input as a polarization transformation, and a codeword d of length N is obtained through logical operations. To reduce the storage overhead, this application proposes a data processing method based on Gray mapping to calculate the subchannel reliability online and determine the information bit position.

[0030] Referring to Fig. 2, Fig. 2 shows a schematic diagram of the architecture of a communication system to which the embodiments of the present application are applied. The communication system shown in Fig. 2 includes a first transmission node 110 and a second transmission node 120, where the first transmission node 110 is connected to the second transmission node 120, and the first transmission node 110 transmits an encoded data sequence to the second transmission node 120. The first transmission node 110 and the second transmission node 120 may include any of the following devices: a base station (BS), an access point (AP), a nodeB, a gnodeB (generalized nodeB), a radio network controller (RNC), an evolved nodeB (eNB), a base station controller (BSC), a base transceiver station (BTS), a transceiver function (TF), a wireless router, a wireless transceiver, a basic service set (BSS), an extended service set (ESS), or a radio base station (RBS), but embodiments of the present application are not limited thereto.

[0031] In a possible embodiment, the first transmitting node 110 and the second transmitting node 120 may be referred to as an access terminal, user equipment (UE), subscriber unit, subscriber station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, wireless communication device, user agent, or user device. For example, the first transmitting node 110 and the second transmitting node 120 may be, but are not limited to, a mobile phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a wearable device, or a terminal device in a 5G network or a future 5G or higher network.

[0032] A first aspect of the present embodiment provides a data processing method applicable to the first transmission node 110 shown in Fig. 2, and Fig. 3 is a flowchart of the data processing method according to the first aspect of the present embodiment. As shown in Fig. 3, this data processing method includes the following steps S100 to S400, and each step will be described in turn below.

[0033] Step S100: Obtain an information bit sequence, where the information bit sequence includes K information bits, where K is an integer greater than 0.

[0034] Step S200: According to the Gray mapping rule, map the information bits in the information bit sequence into an information and frozen bit sequence, where the information and frozen bit sequence includes N bits, where N represents the number of polarization subchannels, and N is an integer greater than K.

[0035] Step S300: Encode the information and the frozen bit sequence to obtain an encoded data sequence.

[0036] Step S400: Transmit the encoded data sequence.

[0037] Illustratively, the information bit sequence is a=[a0, a1, ..., a K-1 ], and the information and frozen bit sequence can be expressed as u = [u0,u1,...,u N-1 ], and the coded data sequence may be represented as d=[d0,d1,...,d N-1 In the embodiment of the present application, the information bits in the information bit sequence a are mapped to the information and frozen bit sequence u according to the Gray mapping rule, and then the information and frozen bit sequence u is encoded to obtain the encoded data sequence d. By determining the sub-channel transmission information bits or frozen bits online using the Gray mapping method and then encoding the information and frozen bit sequence, it is possible to reduce the storage overhead and the computational resources required to obtain the sub-channel reliability.

[0038] For example, step S200 of mapping information bits in an information bit sequence to information and frozen bit sequences according to the Gray mapping rule can be specifically realized by the following steps S210 to S240.

[0039] Step S210: Map the information bits in the information bit sequence to the initial information and frozen bit sequence.

[0040] Step S220: Determine a subchannel reliability value corresponding to each polarization subchannel according to the Gray mapping rule, the natural order subchannel index number, and the quantization weight value sequence.

[0041] Step S230: Determine information and frozen bit indications corresponding to each polarization subchannel according to the subchannel reliability values ​​and reliability thresholds corresponding to each polarization subchannel.

[0042] Step S240: Update the initial information and frozen bit sequence according to the information and frozen bit indication corresponding to each polarization sub-channel to obtain the information and frozen bit sequence.

[0043] Exemplarily, the step S210 of mapping the information bits in the information bit sequence to the initial information and frozen bit sequence can be realized by any of the following manners, but is not limited thereto.

[0044] Method 1: j-th information bit a in the information bit sequence j g of the initial information and frozen bit sequence N-K+j th position, j is an integer between 0 and K-1, and g N-K+j represents the Gray code decimal number corresponding to (N-K+j).

[0045] Method 2: The (K-1-j)th information bit a in the information bit sequence K-1-j , the initial information and the frozen bit sequence g N-K+j th position, where j is an integer between 0 and K-1, and g N-K+j represents the Gray code decimal number corresponding to (N-K+j).

[0046] Method 3: j-th information bit a in the information bit sequence j , the initial information and the frozen bit sequence g j th position, j is an integer between 0 and K-1, and g j is the Gray code decimal number corresponding to j.

[0047] Method 4: The (K-1-j)th information bit a in the information bit sequence K-1-j , the initial information and the frozen bit sequence g j th position, j is an integer between 0 and K-1, and g j is the Gray code decimal number corresponding to j.

[0048] Illustratively, step S220 of determining a subchannel reliability value corresponding to each polarization subchannel based on the Gray mapping rule, the natural order subchannel index number, and the quantization weight value sequence includes at least one of the following steps S221 and S223.

[0049]

number

[0050]

number

number

[0051]

number

[0052]

number

[0053]

number

[0054]

number

[0055] Illustratively, step S230 of determining information and frozen bit indications corresponding to each polarization subchannel based on the subchannel reliability value and reliability threshold corresponding to each polarization subchannel includes: if the subchannel reliability value corresponding to the polarization subchannel is equal to or greater than the reliability threshold, setting the information and frozen bit indications corresponding to the polarization subchannel to a first indication value indicating that the polarization subchannel bears an information bit; and if the subchannel reliability value corresponding to the polarization subchannel is less than the reliability threshold, setting the information and frozen bit indications corresponding to the polarization subchannel to a second indication value indicating that the polarization subchannel bears a frozen bit.

[0056] Illustratively, the initial information and frozen bit sequence is u=[u0,u1,...,uN-1 ], and step S240 of updating the initial information and frozen bit sequence according to the information and frozen bit instructions corresponding to each polarization subchannel to obtain the information and frozen bit sequence may specifically include the following steps:

[0057] Traverse each natural order subchannel index number in forward or reverse order, and for the currently traversed natural order subchannel index number i: g i obtaining information and a frozen bit indication corresponding to the th polarization sub-channel; g i When the information and frozen bit indication corresponding to the th polarization subchannel is the first indication value, i The bit in the gth position in u k Step to adjust to the second position, or g i If the information and frozen bit indication corresponding to the th polarization subchannel is the second indication value, then i performing the step of setting the bit in the th position to 0; Once all natural order subchannel index numbers have been traversed, obtaining the information and frozen bit sequence. Here, k represents an information bit index, and k is an integer between 0 and K-1, or an integer between N-K and N-N. i represents the Gray code decimal number corresponding to i, and g k represents the Gray code decimal number corresponding to k.

[0058] Note that in this embodiment, the quantization weight sequence is represented by β, where β includes n quantization weights, and the j-th quantization weight in β is β j represents a quantization weight value corresponding to the j-th bit in the binary form of the sub-channel index number, where j is an integer between 0 and n-1. i The binary format of g i =bn-1 b n-2 … is represented as b2b1b0, where the 0th bit b0 is the least significant bit, and the (n - 1)th bit b n-1 is the most significant bit. In this case, β j is the quantization weight value corresponding to b j and b j represents the jth bit in the binary form of the subchannel index number g i , where j ∈ {0, 1, …, n}, n = log2N, N is the number of polarization subchannels, and g i represents the Gray code decimal number corresponding to i.

[0059] The n quantization weight values in the quantization weight value sequence are arranged in ascending or descending order. The quantization weight value sequence β, when arranged in ascending order, can be represented as β = [β0, β1, …, β n-1 , and when arranged in descending order, can be represented as β = [β n-1 , β n-2 , …, β0].

[0060] The sum of all the quantization weight values in the quantization weight value sequence β is smaller than the first numerical value, where the first numerical value is represented by M. That is, β n-1 + β n-2 + … + β0 < M. Note that M is a positive integer power of 2. Exemplarily, the value of the first numerical value includes any one of 256, 512, 1024, 2048, or 4096.

[0061] There are two methods for determining the quantization weight value sequence.

[0062] <​​​​​​​​​​​​In the second method, the difference number between the quantized polarization weight value sequence (quantized PW sequence) obtained by the quantized weight value sequence and the polarization weight value sequence (PW sequence) is determined based on a constraint that the difference number is equal to or less than a second value D. Here, the second value D is an integer between 0 and N. M=2 l (l is a positive integer) and M=2 l , only one bit is stored for each confidence threshold, and the element β in β j is a positive integer, j∈{0,1,...,n}, n=log2N, and D is an integer between 0 and N, inclusive.

[0064] As an example, the quantization weight value sequence β may include any of the following: β=[96,81,68,57,48,40,34,28,24,20], or β = [197,165,139,116,98,82,68,58,49,41], or β = [389,327,275,231,194,163,137,115,97,82], or β = [780,656,552,464,390,328,276,232,195,164], or β = [51,43,36,30,25,21,18,15,13], or β = [101, 85, 71, 60, 50, 42, 35, 30, 25], or β = [206,173,145,122,102,86,73,61,51], or β=[480,404,340,286,240,202,170,143,120]

[0065] For example, the reliability threshold in the embodiments of the present application may be obtained from a predetermined mapping relationship based on an index value, where the index value is determined based on at least one of the number of information bits K, the number of polarization subchannels N, and the code rate R, and the mapping relationship includes, but is not limited to, at least one of a mapping formula, a mapping table, or a mapping map. Of course, the mapping relationship may be other expressions having a corresponding relationship, and is not limited to these in the embodiments of the present application.

[0066] In one possible implementation, the information bit sequence a=[a0, a1, ..., a K-1 ], from the natural order subchannel index number i through Gray mapping, the subchannel index number after Gray mapping is g i and then, based on the quantized weight value sequence, i Calculate the reliability value of the th subchannel, obtain the reliability threshold based on the mapping relationship, and i Compare the reliability value of the th subchannel with the reliability threshold, and i Determine whether the th subchannel bears information bits, and determine whether the th subchannel bears information bits and freezes the information and freeze bit sequence u=[u0,u1,...,u N-1 ] and further encode the information and frozen bit sequence u to obtain encoded data d=[d0,d1,...,d N-1 ] may be obtained.

[0067] The information bit sequence and the information and frozen bit sequence have a mapping relationship u f1(j) =a f2(j) where f1 is a function of j and is determined by, but not limited to, f2(j), Gray mapping, information and frozen bit indication, and information index number, where f1(j)∈{0,1,...,N-1}. f2 is a function of j, including but not limited to, f(j)=j, f(j)=Kj, and f2(j)∈{0,1,...,K-1}, where j=0,1,...,K-1. Based on the above mapping relationship, the obtained information bit sequence a=[a0,a1,...,a K-1], the information and frozen bit sequence u=[u0,u1,…,u N-1 ] can be determined.

[0068] Illustratively, the natural order subchannel index numbers take on values ​​in ascending order of 0, 1, 2, ..., N-1. Alternatively, the natural order subchannel index numbers take on values ​​in descending order of N-1, N-2, N-3, ..., 0.

[0069] For example, the subchannel index numbers corresponding to the N polarization subchannels may be arranged in ascending or descending order to obtain a natural order subchannel index number sequence [0, 1, ..., N-1] or [N-1, N-2, ..., 0]. Then, each natural order subchannel index number in the natural order subchannel index number sequence is traversed, and each time a natural order subchannel index number i is traversed, the subchannel index number g corresponding to the natural order subchannel index number i is obtained. i and determining the subchannel reliability values ​​of the currently traversed g based on the information and the frozen bit indications. i The Nth polarization subchannel determines whether the bit carried by the Nth polarization subchannel is an information bit or a frozen bit, and updates the information and frozen bit sequences. After traversing the N polarization subchannels, the final information and frozen bit sequences are obtained.

[0070] Illustratively, the step of encoding the information and the frozen bit sequence to obtain the coded data sequence includes the steps of: obtaining an n-th order serial encoder for performing n-th order serial encoding, and encoding two bits in the information and the frozen bit sequence as a group for each serial encoding; and encoding the information and the frozen bit sequence by the n-th order serial encoder to obtain the coded data sequence.

[0071] Hereinafter, the data processing method according to the embodiments of the present application will be described using several specific examples. Example 1

[0072]

Number

[0073] Exemplarily, the information bits in the information bit sequence a are set to the initial information and the frozen bit sequence u in any of the following ways.

[0074]

Number

[0075] Step 1: Set the information bits in the information bit sequence in ascending order to the K bits after the initial information and the frozen bit sequence. For the information bit sequence a = [a0, a K-1 , when setting the information bits to the K bits after the information and the frozen bit sequence in ascending order, u = [u0, u1, …, u[[ID=2⑨]]<00001②⑦> = [0, …, 0, a0, a1, …, a K-1 is obtained, N represents the number of polarization subchannels, its value is a positive integer power of 2, K is the number of information bits, its value is a positive integer, and K < N is satisfied.

[0076] Step 2: Update the initial information and the frozen bit sequence u = [u0, u1, …, u N-1 = [0, …, 0, a0, a1, …, a[[ID=③⑨]]<00001④0> according to Gray mapping. Updating includes adjusting the element u i at the i-th position in u before updating to the g i -th position, and g i is the Gray code decimal corresponding to i. Exemplarily, for the logical code in which the element u i at the i-th position is adjusted to the g[[ID=④⑨]]<00001④⑤>-th position by the update, reference may be made to the implementation of the logical code shown in FIG. 4.

[0077] In an executable embodiment, the result of Method 1 may be obtained by the following steps. Specifically, the information bit sequence a = [a0, a1, …, a K-1 is stored using a K-bit cache, and the j-th element a j in a is adjusted to the g N-K+j position in the information and frozen bit sequence u. Specifically, for the initialization process of the information and frozen bit sequence u, reference may be made to the logic code shown in FIG. 5.

[0078]

Number

[0079] Step 1: Set the information bits in the information bit sequence in reverse order to the last K bits of the initial information and frozen bit sequence. For the information bit sequence a = [a0, a1, …, a K-1 , when setting the information bits in the information bit sequence in reverse order to the last K bits of the initial information and frozen bit sequence, the initial information and frozen bit sequence u = [u0, u1, …, u N-1 = [0, …, 0, a K-1 , a K-2 , …, a0] is obtained, where N represents the number of polarization sub-channels, its value is a positive integer power of 2, K is the number of information bits, its value is a positive integer, and K < N is satisfied.

[0080] Step 2: Update the initial information and frozen bit sequence u = [u0, u1, …, u N-1 = [0, …, 0, a K-1 , a K-2 , …, a0] according to Gray mapping. The update includes adjusting the element u<00​​​​​​​i The logical code adjusted to the th position may refer to the implementation of the logical code shown in FIG. 4.

[0081] In one executable embodiment, the result of Method 2 may also be obtained by the following steps. Specifically, the information bit sequence a = [a0, a1, …, a K-1 is stored using a K-bit cache, and the (K-1-j)th element a K-1-j in a is adjusted to the g N-K+j th position in the information and frozen bit sequence u. Specifically, for the initialization process of the information and frozen bit sequence u, reference may be made to the logical code shown in FIG. 6.

[0082]

Number

[0083] Step 1: Set the information bits in the information bit sequence in ascending order to the first K bits of the initial information and frozen bit sequence. For the information bit sequence a = [a0, a1, …, a K-1 , when setting the information bits in ascending order to the first K bits of the information and frozen bit sequence, the initial information and frozen bit sequence u = [u0, u1, …, u N-1 = [a0, a1, …, a K-1 , 0, …, 0] is obtained, where N represents the number of polarization subchannels, its value is a positive integer power of 2, K is the number of information bits, its value is a positive integer, and K < N is satisfied.

[0084] Step 2: Update the initial information and frozen bit sequence u = [u0, u1, …, u N-1 = [a0, a1, …, a K-1 , 0, …, 0] according to Gray mapping. Before updating, the element u i at the i-th position in u is adjusted to the g i th position, including adjusting the g iis the Gray code decimal number corresponding to i. Exemplarily, by the update, the i-th position element u i becomes g i The logical code adjusted to the j-th position may refer to the implementation of the logical code shown in FIG. 4.

[0085] In one executable embodiment, the result of Method 3 may also be obtained by the following steps. Specifically, the information bit sequence a = [a0, a1, …, a K-1 is stored using a K-bit cache, and the j-th element a j in a is adjusted to the g j position in the information and frozen bit sequence u. Specifically, for the initialization process of the information and frozen bit sequence u, reference may be made to the logical code shown in FIG. 7.

[0086]

Number

[0087] Step 1: Set the information bits in the information bit sequence in reverse order to the first K bits of the initial information and frozen bit sequence. For the information bit sequence a = [a0, a1, …, a[[ID=​​​​​​​​​​​​​​​​​​​i Adjusting to the second position includes i is the Gray code decimal number corresponding to i. Illustratively, the update will update the i-th position element u i G i The logic code adjusted to the th position may refer to the implementation of the logic code shown in Figure 4.

[0089] In one possible embodiment, the result of Scheme 4 may also be obtained by the following steps: K-1 ] is stored using a K-bit cache, and the (K-1-j)th element a in a is K-1-j The information and the frozen bit sequence u in g j Specifically, the initialization process of the information and frozen bit sequence u may be referred to as the logic code shown in FIG.

[0090] When the information bit sequence is initially stored in the information and frozen bit sequence according to the above rules, the information index number and the information and frozen bit indication are used to determine the i When calculating the reliability value of the th sub-channel, the reliability value of the next sub-channel can be obtained by simple calculation using the reliability value of the previous sub-channel, thereby saving calculation resources. Example 2

[0091] Based on the index value, a confidence threshold w is calculated from the predefined mapping relationship. th In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N, and the mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a mapping table (hereinafter referred to as a reliability threshold table).

[0092] Exemplarily, N is a positive integer power of 2 and includes, but is not limited to, any one of 32, 64, 128, 256, 512, 1024. K is a positive integer and includes, but is not limited to, any one of 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, 299. w K,N is M, where M is a positive integer power of 2, and the value of M includes, but is not limited to, one of 256, 512, 1024, 2048, 4096. Referring to Table 3, Table 3 is a reliability threshold table executable by the K and N indexes. In some other examples, the reliability threshold table includes at least one row or at least one column of Table 3. Table 3 is only one mapping form of the executable reliability threshold table, and other mapping forms may be used, and this is not particularly limited in this embodiment.

[0093]

Table 3

[0094] The relationship of the change in the reliability threshold with respect to the number of information bits K and the relationship of the change in the reliability threshold with respect to the number of polarization sub-channels N can be obtained from the reliability threshold table, and the corresponding reliability threshold for a combination of a certain value of K and a certain value of N is NaN, w K,N includes any one of, where "NaN" is a NULL value indicating that there is no reliability threshold for the current combination of K and N, and w K,N is the reliability threshold for the combination of K and N.

[0095] When the value of K is greater than or equal to the value of N, the reliability threshold corresponding to the value of K and the value of N is NaN, indicating that the reliability threshold is NULL.

[0096] Also, when the value of K is less than the value of N, the reliability threshold corresponding to the value of K and the value of N is w K,Nwhere, in one possible embodiment, w K,N The value of is determined by the following steps S610 to S613.

[0097] Step S610: Calculate subchannel reliability values ​​corresponding to the polarization subchannels according to the quantization weight value sequence β and the subchannel index numbers i corresponding to each polarization subchannel respectively.

[0098] Step S611: Obtain a subchannel reliability sequence based on the subchannel reliability values ​​corresponding to the N polarization subchannels.

[0099] Step S612: Select the K largest subchannel reliability values ​​from the subchannel reliability sequence.

[0100] Step S613: From the K maximum subchannel reliability values, select the minimum subchannel reliability value as w K,N Select as.

[0101] That is, based on the quantization weight value sequence β and the subchannel index number i, N subchannel reliability values ​​w′=[w′0, w′1, …, w′ N-1 ], select the largest K reliability values ​​from w', and select the smallest w from the largest K reliability values. N-K Select w N-K is the element value at the (N, K) position in the confidence threshold table.

[0102] Illustratively, the reliability threshold w' of the i-th subchannel i is determined by Equation 7 below.

number

[0103] For any value of N, there are corresponding K1 and K2, which represent two different values ​​of K. If K1 is smaller than K2, then w K2,N Bigger than w K1,N exists and w K1,N represents the confidence threshold corresponding to the value of K1 and the value of N, and w K2,N represents the confidence threshold corresponding to the value of K2 and the value of N.

[0104] For any value of K, there are corresponding N1 and N2, which represent two distinct values ​​of N. If N1 is smaller than N2, then w K,N2 smaller than w K,N1 exists and w K,N1 represents the confidence threshold corresponding to the value of K and the value of N1, and w K、N2 represents the confidence threshold corresponding to the value of K and the value of N2. Example 3

[0105] Based on the index value, a confidence threshold w is calculated from the predefined mapping relationship. th In this example, the index value is determined based on the value of the number of information bits K and the value of the code rate R, and the mapping relationship between the number of information bits K, the code rate R, and the reliability threshold is recorded in a mapping table (hereinafter referred to as a reliability threshold table).

[0106] Exemplarily, R is a real number greater than 0 and less than 1, and includes, but is not limited to, one of 25 / 32, 25 / 64, 25 / 128, 25 / 256, 25 / 512, 25 / 1024, 35 / 64, 35 / 128, 35 / 256, 35 / 512, 35 / 1024, 43 / 64, 43 / 128, 43 / 256, 43 / 512, 43 / 1024, 51 / 64, 51 / 128, 51 / 256, 51 / 512, 51 / 1024, 59 / 64, 59 / 128, 59 / 256, 59 / 512, 59 / 1024. K is a positive integer and includes, but is not limited to, one of 25, 35, 43, 51, 59. w K,R is M, where M is a positive integer power of 2, and the value of M includes, but is not limited to, one of 256, 512, 1024, 2048, 4096. The reliability threshold table indexed by K and R is shown in Table 4. In another example, the reliability threshold table includes at least one row or at least one column of Table 4. Table 4 is only one mapping form of the executable reliability threshold table, and other mapping forms may be used. In this embodiment, it is not particularly limited.

[0107] [Table 4] ​​​​​​​​​​​​​​​​​Also, when K is smaller than K / R, the confidence threshold corresponding to the value of K and the value of R is w K,R and in one possible embodiment, w K,R The value of is determined by the following steps S620 to S623.

[0111] Step S620: Based on the values ​​of K and R, the value of N is determined.

[0112] Step S621: Calculate a subchannel reliability value corresponding to each polarization subchannel according to the quantization weight value sequence β and the subchannel index number i corresponding to the N polarization subchannels respectively.

[0113] Step S622: Obtain a subchannel reliability sequence based on the subchannel reliability values ​​corresponding to the N polarization subchannels, and select K largest subchannel reliability values ​​from the subchannel reliability sequence.

[0114] Step S623: Select the smallest subchannel reliability value from the K largest subchannel reliability values, and denote the smallest subchannel reliability value as w K,R Let's say.

[0115] That is, first, the number of polarization subchannels N is determined based on the number of information bits K and the code rate R, and illustratively N=K / R. Next, based on the quantization weight value sequence β and the subchannel index number i, N subchannel reliability values ​​w′=[w′0, w′1, ..., w′ N-1 ] is calculated. The largest K reliability values ​​are selected from w', and then the smallest w N-K Select w N-K is the element value at the (R, K) position in the confidence threshold table.

[0116] For any value of K, there are corresponding R1 and R2, which represent two different values ​​of R. If R1 is smaller than R2, then w K,R2 Bigger than w K,R1exists and w K,R1 represents the confidence threshold corresponding to the value of K and the value of R1, and w K,R2 represents the confidence threshold corresponding to the value of K and the value of R2.

[0117] For any value of K, there are corresponding R1 and R2, which represent two different values ​​of R. If R1 is smaller than R2, then w K,R2 Bigger than w K,R1 exists and w K,R1 represents the confidence threshold corresponding to the value of K and the value of R1, and w K,R2 represents the confidence threshold corresponding to the value of K and the value of R2. Example 4

[0118] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0119] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2 ,…,β0]=[96,81,68,57,48,40,34,28,24,20] and n=10. N is a positive integer power of 2, including but not limited to, 32, 64, 128, 256, 512, and 1024. K is a positive integer, including but not limited to, 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 5, and in another example, the confidence threshold table includes at least one row or at least one column of Table 5.

[0120] [Table 5] Example 5

[0121] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0122] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2 ,…,β0]=[197,165,139,116,98,82,68,58,49,41] and n=10. N is a positive integer power of 2, including but not limited to, 32, 64, 128, 256, 512, and 1024. K is a positive integer, including but not limited to, 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 6, and in another example, the confidence threshold table includes at least one row or at least one column of Table 6.

[0123] [Table 6] Example 6

[0124] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0125] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2 ,…,β0]=[389,327,275,231,194,163,137,115,97,82] and n=10. N is a positive integer power of 2, including but not limited to 32, 64, 128, 256, 512, and 1024. K is a positive integer, including but not limited to 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 7, and in another example, the confidence threshold table includes at least one row or at least one column of Table 7.

[0126] [Table 7] Example 7

[0127] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0128] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2,…,β0]=[780,656,552,464,390,328,276,232,195,164] and n=10. N is a positive integer power of 2, including but not limited to 32, 64, 128, 256, 512, or 1024. K is a positive integer, including but not limited to 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, or 299. A specific example of a confidence threshold table is shown in Table 8, and in another example, the confidence threshold table includes at least one row or at least one column of Table 8.

[0129] [Table 8] Example 8

[0130] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0131] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2,...,β0] = [51, 43, 36, 30, 25, 21, 18, 15, 13] and n = 9. N is a positive integer power of 2, including but not limited to, 32, 64, 128, 256, and 512. K is a positive integer, including but not limited to, 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 9. In another example, the confidence threshold table includes at least one row or at least one column of Table 9.

[0132] [Table 9] Example 9

[0133] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0134] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2, ...,β0] = [101, 85, 71, 60, 50, 42, 35, 30, 25] and n = 9. N is a positive integer power of 2, including but not limited to, any of 32, 64, 128, 256, and 512. K is a positive integer, including but not limited to, any of 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 10; in another example, the confidence threshold table includes at least one row or at least one column of Table 10.

[0135] [Table 10] Example 10

[0136] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0137] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2, ...,β0] = [206, 173, 145, 122, 102, 86, 73, 61, 51], and n = 9. N is a positive integer power of 2, including but not limited to, 32, 64, 128, 256, and 512. K is a positive integer, including but not limited to, 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 11, and in another example, the confidence threshold table includes at least one row or at least one column of Table 11.

[0138] [Table 11] Example 11

[0139] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the number of polarization subchannels N. The mapping relationship between the number of information bits K, the number of polarization subchannels N, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0140] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2,…,β0]=[480, 404, 340, 286, 240, 202, 170, 143, 120] and n=9. N is a positive integer power of 2, including but not limited to 32, 64, 128, 256, and 512. K is a positive integer, including but not limited to 25, 35, 43, 51, 59, 67, 75, 83, 91, 99, 107, 115, 123, 131, 139, 147, 155, 163, 171, 179, 187, 195, 203, 219, 235, 251, 267, 283, and 299. A specific example of a confidence threshold table is shown in Table 12, and in another example, the confidence threshold table includes at least one row or at least one column of Table 12.

[0141] [Table 12] Example 12

[0142] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the code rate R, and the mapping relationship between the number of information bits K, the code rate R, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0143] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2,…,β0]=[97,165,139,116,98,82,68,58,49,41], and n=10. R is a real number greater than 0 and less than 1, including, but not limited to, any of the following: 25 / 32, 25 / 64, 25 / 128, 25 / 256, 25 / 512, 25 / 1024, 35 / 64, 35 / 128, 35 / 256, 35 / 512, 35 / 1024, 43 / 64, 43 / 128, 43 / 256, 43 / 512, 43 / 1024, 51 / 64, 51 / 128, 51 / 256, 51 / 512, 51 / 1024, 59 / 64, 59 / 128, 59 / 256, 59 / 512, and 59 / 1024. K is a positive integer, including, but not limited to, any of 25, 35, 43, 51, and 59. A specific example of a confidence threshold table is shown in Table 13, and in another example, the confidence threshold table includes at least one row or at least one column of Table 13.

[0144] [Table 13] Example 13

[0145] Based on the index value, a reliability threshold is obtained from a predetermined mapping relationship. In this example, the index value is determined based on the value of the number of information bits K and the value of the code rate R, and the mapping relationship between the number of information bits K, the code rate R, and the reliability threshold is recorded in a reliability threshold table, and the elements in the reliability threshold table are determined based on the quantization weight value sequence β.

[0146] Illustratively, the quantization weight sequence β=[β n-1 ,β n-2,…,β0]=[480, 404, 340, 286, 240, 202, 170, 143, 120] and n=9. R is a real number greater than 0 and less than 1, including but not limited to: 25 / 32, 25 / 64, 25 / 128, 25 / 256, 25 / 512, 35 / 64, 35 / 128, 35 / 256, 35 / 512, 43 / 64, 43 / 128, 43 / 256, 43 / 512, 51 / 64, 51 / 128, 51 / 256, 51 / 512, 59 / 64, 59 / 128, 59 / 256, and 59 / 512. K is a positive integer, including but not limited to: 25, 35, 43, 51, and 59. A specific example of a confidence threshold table is shown in Table 14, and in another example, the confidence threshold table includes at least one row or at least one column of Table 14.

[0147] [Table 14] Example 14

[0148]

number

[0149]

number

[0150] Here, the binary form of i+1 is i+1=B n-1 B n-2 …B2B1B0, and B j represents the j-th bit that converts integer i+1 into binary form, and its value is bit 0 or bit 1, j∈{0,1,…,n-1}, and e is the B n-1 B n-2 …B2B1B0, the position from the 0th bit B0 to the first bit 1 (i.e., B e =1 and B e-1 =B e-2 =…=B0=0), and B e is the bit value at that position, and B e+1 is the bit value of the e+1th bit, and β e is the e-th element in the quantization weight value sequence β, e∈{0, 1, ..., n-1}.

[0151] In the above embodiment, g is calculated by the following formula: i Compared with calculating the reliability value of the th subchannel, the reliability value of the next subchannel can be quickly obtained based on the reliability value of the previous subchannel, thereby reducing the number of multiplication operations and the amount of calculation.

number

[0152] The quantization weight value sequence β is a descending sequence of positive integers β = [β n-1 , β n-2 , …, β0], or a ascending sequence of positive integers β = [β0, β1, …, β n-1 , and includes either one of them.

[0153] The characteristics of the quantization weight value sequence β include, but are not limited to, that the quantization weight value sequence β includes n quantization weight values, and β j is the quantization weight value corresponding to B j . Here, n = log2N, N is the number of polarization subchannels, j ∈ {0, 1, 2, …, n - 2, n - 1}, and B j represents the j-th bit when converting the integer i into binary form, i = B n-1 B n-2 …B2B1B0, and the 0-th bit B0 is the least significant bit, and the (n - 1)-th bit B n-1 is the most significant bit.

[0154] The quantization weight value sequence β = [β n-1 , β n-2 , …, β0] satisfies β n-1 + β n-2 + … + β0 < M, where M is a positive integer power of 2. Specifically, the value of M includes at least one of 256, 512, 1024, 2048, 4096.

[0155] The quantization weight value sequence β = [β n-1 , β n-2 , …, β0] means that the quantization weight value sequence is preset, and the sum of the elements β<​​It is determined by at least one of the following constraints: the sum β j +…+β0<M, and the number of differences between the quantized PW sequence obtained based on the quantized weight value sequence and the PW sequence is not more than a second numerical value D. Here, M is a positive integer power of 2, and the value of M includes, but is not limited to, any of 256, 512, 1024, 2048, and 4096. β j is a positive integer, j ∈ {0, 1, 2, …, n - 2, n - 1}, n = log2N, and D is an integer greater than or equal to 0 and less than N.

[0156] When the value of D is small, the number of differences between the obtained quantized PW sequence and the PW sequence is small, but a larger M is required to store the quantized PW sequence, that is, more storage space is required to store the reliability threshold. When the value of D is large, the number of differences between the obtained quantized PW sequence and the PW sequence is large, and a large M is not required to store the quantized PW sequence, that is, only a small amount of storage space is required to store the reliability threshold. By adjusting the size of D, various application scenarios can be satisfied.

[0157] In one example, M = 256, N = 512, n = 9, D = 254, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [51, 43, 36, 30, 25, 21, 18, 15, 13], where the sum of the elements in the quantized weight value sequence β, β n-1 +β n-2 +…+β0 = 252 < M. Based on the quantized weight value sequence β, the reliability value w ’ i of the i-th subchannel is calculated for i = 0, 1, …, N - 1. The N subchannel reliability values are sorted in descending order, and based on the sorted index values, PW’ = [PW N-1 , PW N-2 , …, PW0] is obtained, where PW N-1 ​​​represents the sub-channel index number corresponding to the largest reliability value, and PW0 represents the sub-channel index number corresponding to the smallest reliability value. Reverse the PW' sequence to obtain the quantized PW sequence PW quan =[PW0, PW1, …, PW N-1 . The result of comparing the quantized PW sequence (PW quan ) obtained by the parameters with the PW sequence (PW) shows that the difference number between the two is 254, which is less than or equal to D. That is, at 254 positions, PW quan (i) ≠ PW(i), where i = 0, 1, …, N - 1.

[0158] In another example, M = 512, N = 512, n = 9, D = 76, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [101, 85, 71, 60, 50, 42, 35, 30, 2​​​​​​​​​​​​​​​​​​​​​​​In yet another example, M = 1024, N = 512, n = 9, D = 6, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [206, 173, 145, 122, 102, 86, 73, 61, 51], where the sum of the elements in the quantized weight value sequence β, β n-1 + β n-2 + … + β0 = 1019 < M. Based on the quantized weight value sequence β, the reliability value w ’ i of the i-th subchannel is calculated for i = 0, 1, …, N - 1. The N subchannel reliability values are sorted in descending order, and based on the sorted index values, PW’ = [PW N-1 , PW N-2 , …, PW0] is obtained, where PW N-1 represents the subchannel index number corresponding to the largest reliability value, and PW0 represents the subchannel index number corresponding to the smallest reliability value. The PW’ sequence is reversed to obtain the quantized PW sequence PW quan = [PW0, PW1, …, PW N-1 . Comparing the quantized PW sequence (PW quan ) obtained by the parameters with the PW sequence (PW), the difference number between the two is 6, which is less than or equal to D. That is, there are 6 positions where PW quan (i) ≠ PW(i) for i = 0, 1, …, N - 1.

[0160] In a further example, M = 4096, N = 512, n = 9, D = 0, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [480, 404, 340, 286, 240, 202, 170, 143, 120], where the sum of the elements in the quantized weight value sequence β, β n-1 + β n-2 + … + β0 = 2385 < M. Based on the quantized weight value sequence β, the reliability value w<​Calculate, where \(i = 0, 1, \ldots, N - 1\). Sort the \(N\) sub - channel reliability values in descending order, and based on the sorted index values, \(PW'=[PW N-1 ,PW N-2 ,\ldots,PW0]\) is obtained, where \(PW N-1 \) represents the sub - channel index number corresponding to the largest reliability value, and \(PW0\) represents the sub - channel index number corresponding to the smallest reliability value. Reverse the \(PW'\) sequence to obtain the quantized \(PW\) sequence \(PW quan =[PW0,PW1,\ldots,PW N-1 \). Comparing the quantized \(PW\) sequence \((PW quan )\) obtained by the parameters with the \(PW\) sequence \((PW)\), the difference number between the two is \(0\) and is less than or equal to \(D\), that is, there are \(0\) positions where \(PW quan (i)\neq PW(i)\) for \(i = 0, 1, \ldots, N - 1\).

[0161] In a further example, \(M = 512\), \(N = 1024\), \(n = 10\), \(D = 466\), the quantized weight value sequence \(\beta=[\beta n-1 ,\beta n-2 ,\ldots,\beta0]=[96,81,68,57,48,40,34,28,24,20]\), where the sum of the elements in the quantized weight value sequence \(\beta\), \(\beta n-1 +\beta n-2 +\ldots+\beta0 = 496<M\). Based on the quantized weight value sequence \(\beta\), calculate the reliability value \(w' i \) of the \(i\) - th sub - channel, where \(i = 0, 1, \ldots, N - 1\). Sort the \(N\) sub - channel reliability values in descending order, and based on the sorted index values, \(PW'=[PW N-1 ,PW N-2 ,\ldots,PW0]\) is obtained, where \(PW N-1 \) represents the sub - channel index number corresponding to the largest reliability value, and \(PW0\) represents the sub - channel index number corresponding to the smallest reliability value. Reverse the \(PW'\) sequence to obtain the quantized \(PW\) sequence \(PW quan =[PW0,PW1,\ldots,PW N-1 \). Comparing the quantized \(PW\) sequence \((PW quanAs a result of comparing with the PW sequence (PW), the number of differences between the two is 466, which is less than or equal to D. That is, at 466 positions, PW quan (i)≠PW(i), where i = 0, 1, …, N - 1.

[0162] In a further example, M = 1024, N = 1024, n = 10, D = 70, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [197, 165, 139, 116, 98, 82, 68, 58, 49, 41]. Here, the quantized weight value sequence β satisfies the characteristic that the sum of the elements in the sequence β n-1 + β n-2 + … + β0 = 1013 < M. Based on the quantized weight value sequence β, the reliability value w’ i of the i-th subchannel is calculated, where i = 0, 1, …, N - 1. The N subchannel reliability values are sorted in descending order, and based on the sorted index values, PW’ = [PW N-1 , PW N-2 , …, PW0] is obtained. Here, PW N-1 represents the subchannel index number corresponding to the largest reliability value, and PW0 represents the subchannel index number corresponding to the smallest reliability value. The PW’ sequence is reversed to obtain the quantized PW sequence PW quan = [PW0, PW1, …, PW N-1 . As a result of comparing the quantized PW sequence (PW quan ) obtained by the parameters with the PW sequence (PW), the number of differences between the two is 70, which is less than or equal to D. That is, at 70 positions, PW quan (i)≠PW(i), where i = 0, 1, …, N - 1.

[0163] In a further example, M = 2048, N = 1024, n = 10, D = 24, and the quantized weight value sequence β = [β n-1 , β n-2 , …, β0] = [​​n-2 +…+β0 = 2010 satisfies the characteristics of M. Based on the quantization weight value sequence β, the reliability value w’ of the i-th subchannel i is calculated, where i = 0, 1, …, N - 1. The N subchannel reliability values are sorted in descending order, and based on the sorted index values, PW’ = [PW N-1 , PW N-2 , …, PW0] is obtained, where PW N-1 represents the subchannel index number corresponding to the largest reliability value, and PW0 represents the subchannel index number corresponding to the smallest reliability value. The PW’ sequence is reversed to obtain the quantization PW sequence PW quan = [PW0, PW1, …, PW N-1 . The result of comparing the quantization PW sequence (PW quan ) obtained by the parameter with the PW sequence (PW) shows that the difference number between the two is 24 and is less than or equal to D, that is, at 24 positions, PW quan (i) ≠ PW(i), where i = 0, 1, …, N - 1.

[0164] In a further example, M = 4096, N = 1024, n = 10, D = 0, and the quantization weight value sequence β = [β n-1 , β n-2 , …, β0] = [780, 656, 552, 464, 390, 328, 276, 232, 195, 164], where the sum of the elements in the quantization weight value sequence β, β n-1 + β[[ID=​​​​​​​​​quan =[PW0,PW1,…,PW N-1 ] is obtained by the quantized PW sequence (PW quan ) and the PW sequence (PW), the difference between them is 0, which is less than or equal to D. That is, there is a PW in 0 positions. quan (i)≠PW(i), i=0, 1, ..., N-1. Example 15

[0165] The information and frozen bit indication corresponding to each polarization subchannel is determined based on the subchannel reliability value and the reliability threshold corresponding to each polarization subchannel. A specific implementation process may include: when the subchannel reliability value corresponding to the polarization subchannel is equal to or greater than the reliability threshold, setting the information and frozen bit indication corresponding to the polarization subchannel to a first indication value indicating that the polarization subchannel bears an information bit; and when the subchannel reliability value corresponding to the polarization subchannel is less than the reliability threshold, setting the information and frozen bit indication corresponding to the polarization subchannel to a second indication value indicating that the polarization subchannel bears a frozen bit.

[0166]

number

[0167] The information and frozen bit sequence finally obtained and the information bit sequence have a mapping relationship u f1(j) =a f2(j) where f1 is a function of j, including but not limited to, determined by f2(j), Gray mapping, information and frozen bit indication, information index number, f1(j)∈{0,1,...,N-1}, and f2 is a function of j, including but not limited to, f(j)=j, f(j)=Kj, f2(j)∈{0,1,...,K-1}, where j=0,1,...,K-1.

[0168]

number

[0169] (1) Set the initial value of the information index number k = K - 1, and the Gray code decimal number g corresponding to the initial value of k k refers to the last information bit a in u K-1 .

[0170] <​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0178] (4) When i = N - 1, the update of the information and the frozen bit sequence is completed, and the final information and the frozen bit sequence are obtained.

[0179] Here, N is the number of polarization sub-channels, the value of which is a positive integer power of 2, K is the number of information bits, the value of which is a positive integer, and K < N is satisfied. F = 1 indicates that the i-th sub-channel bears an information bit, and F = 0 indicates that the i-th sub-channel bears a frozen bit. Example 18

[0180]

Number

[0181] (1) Set the initial value of the information index number k = K - 1, and the Gray code decimal number g corresponding to the initial value of k k points to the first information bit a0 in u.

[0182] (2) Set the initial value of the sub-channel index number to g i and i = N - 1.

[0183]

Number

[0184] (4) When i = 0, the update of the information and the frozen bit sequence is completed, and the final information and the frozen bit sequence are obtained.

[0185] Here, N is the number of polarization sub-channels, which is a positive integer power of 2, K is the number of information bits, the value of which is a positive integer, and K < N is satisfied. F = 1 indicates that the i-th sub-channel bears an information bit, and F = 0 indicates that the i-th sub-channel bears a frozen bit. Example 19

[0186]

Number

[0187] (1) Set the initial value k = N - K of the information index number, and the Gray code decimal number g corresponding to the initial value of k points to the last information bit a in u. k is the last information bit a in u. <00​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Specifically, the intermediate coded bits of each stage are stored in the storage space of information and frozen bit sequences, and two bits are calculated in each stage in one group, and the coding process is calculated serially in Stage 0, Stage 1, ..., Stage-1. In this way, by storing the intermediate coded bits of each stage using the storage space of information and frozen bit sequences, the storage overhead can be reduced.

[0193] For example, the information and frozen bit sequences are processed in ascending order of sub-channel index numbers. A specific processing process may include processing in ascending order of sub-channel index numbers, calculating two bits in a group in each stage, storing the intermediate coded bits of each stage in a storage space for the information and frozen bit sequences, and performing the coding process serially in Stage 0, Stage 1, ..., Stage-1. Example 21

[0194] Information and frozen bit sequence u=[u0,u1,…,u N-1 ] to obtain coded data, as shown in FIG. 13, includes the steps of processing the subchannel index numbers i=0, 2, 4, ..., N-2 in ascending order, the steps of calculating two bits at the positions of the subchannel index numbers k0 and k1 in one group at each stage, and the steps of calculating one intermediate coded bit (u k0 +u k1 ) mod 2 at the k0th position of the information and frozen bit sequence u, where j=0, 1, 2, ..., n-1, and the encoding process is calculated serially in Stage 0, Stage 1, ..., Stage n-1, where j represents the polar encoding stage index number.

[0195] where u=[u0,u1,…,u N-1 ] is the information and frozen bit sequence output in step S210, i is the subchannel index number, and i is in binary form i=Bn-1 B n-2 …B j+1 B j B j-1 ...B2B1B0, where B0 is the least significant bit and mod2 means modulo 2. k0 is a decimal number obtained by exchanging the jth bit of i with the least significant bit, and k1 is a decimal number obtained by exchanging the jth bit of i+1 with the least significant bit. In one example, i is an even number, B0=0, and i=B n-1 B n-2 …B j+1 B j B j-1 …B2B1B0, jth bit B of B0 j is exchanged with the least significant bit B0, so k0=B n-1 B n-2 …B j+1 B0B j-1 …B2B1B j In one example, i=10d=1010b, j=3, and swap the j-th bit of i with the least significant bit to get k0=0011b=3d. In one example, if i is even, then i+1=B n-1 B n-2 …B j+1 B j B j-1 ...The least significant bit of B2B1B0 is B0=1, and i+1=B n-1 B n-2 …B j+1 B j B j-1 …jth bit B of B2B1B0 j is exchanged with the least significant bit B0, and k1=B n-1 B n-2 …B j+1 B0B j-1 …B2B1B j In one example, i+1=1011b=11d, j=3, and swap the j-th bit of i+1 with the least significant bit to get k1=1011b=11d. Example 22

[0196] Information and frozen bit sequence u=[u0,u1,…,u N-1] to obtain coded data, as shown in FIG. 14, includes the steps of processing the subchannel numbers i=N-2, N-4, N-6, ..., 0 in ascending order, the steps of calculating two bits at the positions of the subchannel index numbers k0 and k1 in one group at each stage, and the steps of calculating one intermediate coded bit (u k0 +u k1 ) mod 2 at the k0-th position of the information and frozen bit sequence u. In one example, the encoding process is calculated serially in Stage 0, Stage 1, ..., Stage n-1, based on j=0, 1, 2, ..., n-1, where j represents the polar encoding stage index number.

[0197] where u=[u0,u1,…,u N-1 ] is the information and frozen bit sequence output in step S210, i is the subchannel index number, and i is in binary form i=B n-1 B n-2 …B j+1 B j B j-1 ... represents B2B1B0, where B0 represents the least significant bit and mod2 means modulo 2. k0 is a decimal number obtained by exchanging the jth bit of i with the least significant bit, and k1 is a decimal number obtained by exchanging the jth bit of i+1 with the least significant bit.

[0198] A second aspect of the present embodiment provides a data processing method applicable to the second transmission node 120 shown in Fig. 2. The data processing method includes receiving an encoded data sequence transmitted by a transmitter, where the encoded data sequence includes N encoded data and is obtained by mapping information bits in the information bit sequence to information and frozen bit sequences according to a Gray mapping rule and encoding the information and frozen bit sequences to obtain an encoded data sequence, where the information bit sequence includes K information bits, where K is an integer greater than 0, and the information and frozen bit sequences include N bits, where N indicates the number of polarization subchannels, where N is an integer greater than K.

[0199] After receiving the coded data sequence sent by the sender, the coded data sequence can be decoded according to the Gray mapping rule to obtain the original information bit sequence.

[0200] Referring to FIG. 15, the transmitting side (first transmission node 110) generates an information bit sequence a=[a0, a1, . . . , a K-1 ] is the information and frozen bit sequence u=[u0,u1,…,u N-1 ] and encode the information and frozen bit sequence u into the encoded data sequence d=[d0,d1,…,d N-1 ], the receiving side (second transmission node 120) receives the coded data sequence d=[d0, d1, ..., d N-1 ], the coded data sequence d=[d0,d1,…,d N-1 ] to obtain the information and the frozen bit sequence u=[u0,u1,…,u N-1 ] and calculate the information and frozen bit sequence u=[u0,u1,...,u] based on at least one of a Gray mapping rule, a quantization weight value sequence, and a confidence threshold. N-1 ] into the original information bit sequence a=[a0,a1,…,a K-1 ] to restore it.

[0201] The process of restoring the coded data sequence d to the original information bit sequence a is the inverse process of converting the information bit sequence a into the coded data sequence d. The specific implementation principle can refer to the implementation principle of the data processing method according to the first aspect of the embodiment of the present application, and will not be described in detail in the embodiment of the present application.

[0202] A third aspect of an embodiment of the present application provides a data processing device, and referring to FIG. 16, the data processing device comprises: a subchannel and stage calculation means 210 for outputting natural order subchannel index numbers and serial stage index numbers; a confidence threshold memory 220 for storing a confidence threshold; a first Gray code converter 231 for converting the natural order subchannel index numbers into a first Gray code decimal number according to a Gray mapping rule; a quantization weight value sequence memory 240 for storing a quantization weight value sequence; a subchannel reliability calculation means 250 for determining a subchannel reliability value based on the quantization weight value sequence and the natural order subchannel index number; a reliability comparator 260 for comparing the sub-channel reliability value with a reliability threshold and outputting information and a freeze bit indication according to the comparison result; an information bit index calculation means 270 for outputting an information bit index according to the information bit number, the polarization sub-channel number, and the information and frozen bit indication; a second Gray code converter 232 for converting the information bit index into a second Gray code decimal number; an encoded bit information memory 280 for receiving and storing an input information bit sequence, and for determining and storing an information and frozen bit sequence based on the information bit sequence, the first Gray code decimal number, and the second Gray code decimal number; a serial encoder 290 for serially encoding the information and frozen bit sequence based on the serial stage index number and the natural order subchannel index number to output an encoded data sequence; The coded bit information memory 280 is further used to store the coded data sequence.

[0203] The device shown in Fig. 16 may be applied to the first transmission node shown in Fig. 2 as an implementation framework for the first transmission node to process data. The data processing device according to the embodiment of the present application does not directly store the Polar code sequence, but determines the information bit position online to reduce the storage complexity. The Gray code decimal number g corresponding to i is obtained by a Gray code converter. i and then, by using the reliability value of the previous sub-channel, the reliability value of the next sub-channel can be quickly obtained, thereby reducing the number of multiplication operations and the amount of calculation.

[0204] In one example, in the subchannel and stage counter 210, the initial value of the stage index number j is equal to −1, the initial value of the subchannel index number i is equal to 0, and after i is counted from 0 to N−1, the stage index number j is accumulated to 1. In one example, in the subchannel and stage counter 210, the initial value of the stage index number j is equal to −1, the initial value of the subchannel index number i is equal to N−1, and after i is counted down from N−1 to 0, the stage index number j is accumulated to 1. Here, Stage-1 indicates a stage that obtains the information and frozen bit sequence u from the information bit sequence a. Stage0, Stage1, ..., Stage-1 indicate stages that obtain the encoded data sequence d from the information and frozen bit sequence u.

[0205] In one example, the confidence threshold memory 220 stores a confidence threshold w thare stored, and the reliability thresholds have a mapping relationship with parameters including, but not limited to, the information bit sequence size K, the polarization matrix size N, and the code rate R.

[0206] In one example, the first Gray code converter 231 converts the sub-channel index number i into a Gray-mapped sub-channel index number g i Convert to g i is the Gray code decimal number corresponding to i, and its value is an integer greater than or equal to 0 and less than N. In one specific example, i=5, g i = 7, and in another example, i = 6, g i =5.

[0207] In one example, the quantization weight value sequence memory 240 stores a quantization weight value sequence β=[β n-1 ,β n-2 ,...,β0]. In one specific example, the quantization weight value sequence memory stores data of β=[β n-1 ,β n-2 ,…,β0]=[197,165,139,116,98,82,68,58,49,41] is stored.

[0208]

number

[0209]

number

[0210]

number

[0211] In one example, the coded bit information memory 280 stores an information bit sequence a, an information and frozen bit sequence u, and coded data d. In one example, the coded bit information memory 280 initially receives an information bit sequence, and in one specific example, u=[0,...,0,a0,a1,...,a K-1 ] is Gray transformed to obtain the initial information and frozen bit sequence. In one example, the stage index number is j=-1, and after i is counted from 0 to N-1, or after i is counted down from N-1 to 0, the information and frozen bit sequence u=[u0, u1, ..., u N-1 In one example, the stage index number is j=n-1, and the coded data d=[d0, d1, ..., d N-1 ] will be output.

[0212] In one example, the serial encoder 290 encodes the information in the coded bit information memory 280 and the frozen bit sequence data to obtain coded data. In one specific example, i is an even subchannel index number, and binary i=B n-1 B n-2 …B j+1 B j B j-1 …B2B10, k0=B n-1 B n-2 …B j+1 0B j-1 …B2B1B j , k1=B n-1 B n-2 …B j+1 1B j-1 …B2B1B j and the serial encoder 290 encodes the information in the coded bit information memory 280 and the frozen bit sequence u=[u0, u1, ..., u N-1 ], u k0 =(u k0 +u k1 ) mod 2. Update data u k0 is written into the k0th location of the coded bit information memory 280.

[0213] In some embodiments of the present application, the disclosed devices and methods may be realized in other ways. For example, the above device embodiments are merely illustrative, and the division of the modules or units is merely a logical functional division. In actual implementation, other division methods are possible, such as combining multiple units or components, integrating them into another device, or ignoring or not implementing some features. Meanwhile, the shown or discussed couplings or direct couplings or communication connections between each other may be indirect couplings or communication connections via some interfaces, devices, or units, and may be in electrical, mechanical, or other forms.

[0214] In addition, the contents of the information interactions and execution processes between the above devices / units are based on the same concept as the method embodiments of the present application, and therefore, the specific functions and technical effects thereof can be specifically referred to in the method embodiments, and therefore, the description thereof will be omitted here.

[0215] Additionally, although the embodiments herein illustrate operations in a particular order in the figures, this should not be construed as requiring that these operations be performed in the particular order or serial order shown, or that all of the operations shown be performed, to achieve desirable results. In certain environments, multitasking and parallel processing may be advantageous.

[0216] Referring to FIG. 17, a fourth aspect of the present embodiment provides an electronic device 900, which includes: at least one processor 910; at least one memory 920 for storing at least one program, including but not limited to: The at least one program, when executed by the at least one processor 910, performs the data processing method described in any of the above embodiments.

[0217] The processor 910 and memory 920 may be connected by a bus or in some other way.

[0218] The processor 910 may employ a central processing unit (CPU). The processor may also be another general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc. The general-purpose processor may be a microprocessor, any conventional processor, etc. Alternatively, the processor 910 employs one or more integrated circuits for executing related programs to realize the technical solutions according to the embodiments of the present application.

[0219] The memory 920 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs or non-transitory computer-executable programs, such as the data processing methods executed by the electronic device described in any of the embodiments of the present application. The processor 910 can implement the data processing methods by executing the non-transitory software programs and instructions stored in the memory 920.

[0220] The memory 920 may include a program storage area capable of storing an operating system, an application program required for at least one function, and a data storage area capable of storing data required for executing the data processing methods described above. Furthermore, the memory 920 may include high-speed random access memory and may further include non-transitory memory, such as at least one magnetic disk memory device, flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 920 optionally includes memory configured remotely from the processor 910, which may be connected to the processor 910 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0221] The non-transitory software programs and instructions necessary to implement the above data processing methods are stored in memory 920 and, when executed by one or more processors 910, perform the data processing methods according to any embodiment of the present application.

[0222] An embodiment of the present application also provides a computer-readable storage medium storing a processor-executable program for, when executed by a processor, implementing the data processing method described in any of the above embodiments.

[0223] The computer storage medium of the embodiments of the present application may employ any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific (non-exhaustive) examples of computer-readable storage media include an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. As used herein, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, apparatus, or device.

[0224] A computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier that bears computer-readable program code. Such propagated data signals may take various forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0225] The program code contained in the computer readable medium may be transmitted over any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0226] Computer program code for carrying out the operations of the present application may be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may run entirely on the user computer, partially on the user computer, as a separate software package, partially on the user computer, partially on a remote computer, or entirely on a remote computer or server. When a remote computer is involved, the remote computer may be connected to the user computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., connected via the Internet using an Internet Service Provider).

[0227] An embodiment of the present application provides a computer program product storing program instructions which, when run on a computer, causes the computer to perform the data processing method described in any of the above embodiments.

[0228] Although several examples of the present application have been specifically described above, the present application is not limited to the above-described embodiments, and a person skilled in the art may make various equivalent modifications or substitutions under common conditions that do not violate the scope of the present application, and all of these equivalent modifications or substitutions are intended to be included within the scope limited by the present application.

Claims

1. 1. A data processing method comprising: obtaining an information bit sequence, the information bit sequence including K information bits, where K is an integer greater than 0; mapping information bits in the information bit sequence to information and frozen bit sequences according to a Gray mapping rule, wherein the information and frozen bit sequences include N bits, where N represents the number of polarization subchannels, and N is an integer greater than K; encoding the information and the frozen bit sequence to obtain the encoded data sequence; and transmitting the encoded data sequence.

2. said step of mapping information bits in said information bit sequence to information and frozen bit sequences according to a Gray mapping rule; mapping information bits in the information bit sequence to initial information and frozen bit sequences; determining a subchannel reliability value corresponding to each of the polarization subchannels based on the Gray mapping rule, natural order subchannel index numbers, and quantization weight value sequences; determining information and a frozen bit indication corresponding to each of the polarization subchannels based on a subchannel reliability value and a reliability threshold corresponding to each of the polarization subchannels; updating the initial information and frozen bit sequence according to information and frozen bit instructions corresponding to each of the polarization subchannels to obtain the information and frozen bit sequence.

3. The step of mapping information bits in the information bit sequence to initial information and frozen bit sequences comprises: The j-th information bit a in the information bit sequence ｊ of the initial information and the frozen bit sequence Ｎ－Ｋ＋ｊ Set it to the second position, or The (K-1-j)th information bit a in the information bit sequence Ｋ－１－ｊ of the initial information and the frozen bit sequence Ｎ－Ｋ＋ｊ Set it to the second position, or The j-th information bit a in the information bit sequence ｊ of the initial information and the frozen bit sequence ｊ Set it to the second position, or The (K-1-j)th information bit a in the information bit sequence Ｋ－１－ｊ of the initial information and the frozen bit sequence ｊ setting the first position; j is an integer from 0 to K-1, and g ｊ The method of claim 2 , wherein j is the Gray code decimal number corresponding to j.

4. determining a subchannel reliability value corresponding to each of the polarization subchannels based on the Gray mapping rule, natural order subchannel index numbers, and quantization weight value sequences; [Equation 1] or [Equation 2] or [Equation 3] The method of claim 2 , comprising at least one of:

5. The expression for the initial information and frozen bit sequence is u=[u ０ , u １ , ..., u Ｎ－１ ], and the step of updating the initial information and frozen bit sequence according to the information and frozen bit indication corresponding to each of the polarization sub-channels to obtain the information and frozen bit sequence comprises: Traverse each natural order subchannel index number in forward or reverse order, and for the natural order subchannel index number i currently being traversed, ｉ obtaining information and a frozen bit indication corresponding to the th polarization subchannel; ｉ When the information and freeze bit indication corresponding to the th polarization subchannel is a first indication value, g ｉ The bit in the th position of u is ｋ Adjust to the second position, and ｉ When the information and freeze bit indication corresponding to the th polarization subchannel is a second indication value, g ｉ setting the bit in the th position to 0; and obtaining said information and a frozen bit sequence upon completion of traversal of all natural order subchannel index numbers; k represents an information bit index, and k is an integer between 0 and K-1, or an integer between N-K and N; and g ｉ represents the Gray code decimal number corresponding to i, and g ｋ The method of claim 2 , wherein k represents the Gray code decimal number corresponding to k.

6. 3. The method of claim 2, wherein the n quantization weight values ​​in the quantization weight value sequence are arranged in ascending or descending order, and the mth quantization weight value in the quantization weight value sequence represents a quantization weight value corresponding to the mth bit in a binary form of a natural order subchannel index number, where m is an integer between 0 and n-1.

7. 7. The method of claim 6, wherein the sum of all quantization weight values ​​in the sequence of quantization weight values ​​is less than a first number that is a positive integer power of two.

8. The method of claim 7 , wherein the first numerical value comprises one of 256, 512, 1024, 2048, or 4096.

9. The sequence of quantization weight values ​​is presetting the sequence of quantization weight values; or The method of claim 2, wherein the quantization weight value sequence is determined by at least one of the following constraints: the number of differences between the quantized polarization weight value sequence obtained by the quantization weight value sequence and the polarization weight value sequence is less than or equal to a second numerical value, which is an integer greater than or equal to 0 and less than or equal to N.

10. 3. The method of claim 2, wherein the reliability threshold is obtained from a predetermined mapping relationship based on an index value, the index value being determined based on at least one of a value of K, a value of N, and a value of a code rate R, and the mapping relationship includes at least one of a mapping equation, a mapping table, or a mapping map.

11. determining information and a frozen bit indication corresponding to each of the polarization sub-channels based on a sub-channel reliability value and a reliability threshold corresponding to each of the polarization sub-channels, if the subchannel reliability value corresponding to the polarization subchannel is equal to or greater than the reliability threshold, setting the information and frozen bit indication corresponding to the polarization subchannel as a first indication value indicating that the polarization subchannel bears information bits; and if the subchannel reliability value corresponding to the polarization subchannel is less than the reliability threshold, setting the information corresponding to the polarization subchannel and the frozen bit indication to a second indication value indicating that the polarization subchannel is bearing a frozen bit.

12. The expression for the information bit sequence is a=[a ０ , a １ , ..., a Ｋ－１ ], and the expression for the information and frozen bit sequence is u=[u ０ , u １ , ..., u Ｎ－１ ], and the information bit sequence and the information and frozen bit sequence are mapped to a mapping relation u ｆ１（ｊ） = a ｆ２（ｊ） 2. The method of claim 1, wherein f1(j)∈{0, 1, ..., N-1}, f2(j)∈{0, 1, ..., K-1}, j∈{0, 1, ..., K-1}.

13. f1 is a function of j and is determined based on f2(j), Gray mapping, information and frozen bit indication, and information index number; 13. The method of claim 12, wherein f2 is a function of j, including f(j)=j or f(j)=K-j.

14. said step of encoding said information and frozen bit sequence to obtain said encoded data sequence comprises: Obtaining an n-th serial encoder for performing n-th serial encoding, and encoding two bits in the information and frozen bit sequences as one group in each n-th serial encoding, wherein the two bits are represented as the k0th bit and the k1th bit, respectively, where k0 represents a decimal number obtained by exchanging the jth bit of sub-channel i with the least significant bit, k1 represents a decimal number obtained by exchanging the jth bit of sub-channel i+1 with the least significant bit, i∈{0, 2, 4, ..., N-2}, j represents a serial encoding stage, j∈{0, 1, 2, ..., n-1}, and n=log ２ N, and encoding the information and frozen bit sequence with the n-th order serial encoder to obtain the encoded data sequence.

15. 1. A data processing method comprising: receiving a coded data sequence transmitted by a transmitter, the coded data sequence including N coded data; 1. A data processing method, comprising: mapping information bits in an information bit sequence to information and frozen bit sequences according to a Gray mapping rule; and encoding the information and frozen bit sequences to obtain the encoded data sequence; wherein the information bit sequence includes K information bits, where K is an integer greater than 0; and the information and frozen bit sequences include N bits, where N represents the number of polarization subchannels, where N is an integer greater than K.

16. 1. A data processing device, comprising: subchannel and stage calculation means for outputting natural order subchannel index numbers and serial stage index numbers; a confidence threshold memory for storing a confidence threshold; a first Gray code converter for converting the natural order subchannel index numbers into a first Gray code decimal number according to a Gray mapping rule; a quantization weight value sequence memory for storing a quantization weight value sequence; subchannel reliability calculation means for determining a subchannel reliability value based on the quantization weight value sequence and the natural order subchannel index numbers; a reliability comparator for comparing the subchannel reliability value with the reliability threshold and outputting information and a freeze bit indication according to the comparison result; an information bit index calculation means for outputting an information bit index according to the number of information bits, the number of polarization sub-channels, and the information and frozen bit indications; a second Gray code converter for converting the information bit index into a second Gray code decimal number; an encoded bit information memory for receiving and storing an input information bit sequence, and for determining and storing an information and frozen bit sequence based on the information bit sequence, the first Gray code decimal number, and the second Gray code decimal number; a serial encoder for serially encoding the information and frozen bit sequence based on the serial stage index number and the natural order subchannel index number to output an encoded data sequence; A data processing apparatus, wherein said coded bit information memory is further used to store said coded data sequence.

17. An electronic device, at least one processor; at least one memory for storing at least one program; An electronic device that, when at least one of the programs is executed by at least one of the processors, implements the data processing method according to any one of claims 1 to 15.

18. A computer-readable storage medium storing a program executable by a processor, which, when executed by a processor, implements the data processing method according to any one of claims 1 to 15.

19. 1. A computer program product comprising: A computer program product comprising a computer program or computer instructions, the computer program or the computer instructions being stored in a computer-readable storage medium, a processor of a computer device reading the computer program or the computer instructions from the computer-readable storage medium, and the processor executing the computer program or the computer instructions to cause the computer device to perform the data processing method of any one of claims 1 to 15.

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