WO2021208243A1 - 基于多翻转比特集合的极化码置信传播译码方法 - Google Patents

基于多翻转比特集合的极化码置信传播译码方法 Download PDF

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WO2021208243A1
WO2021208243A1 PCT/CN2020/098756 CN2020098756W WO2021208243A1 WO 2021208243 A1 WO2021208243 A1 WO 2021208243A1 CN 2020098756 W CN2020098756 W CN 2020098756W WO 2021208243 A1 WO2021208243 A1 WO 2021208243A1
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flipped
estimated
estimated codeword
codeword
decoding
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张建勇
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北京交通大学
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0052—Realisations of complexity reduction techniques, e.g. pipelining or use of look-up tables
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0057—Block codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0061—Error detection codes

Definitions

  • the present invention relates to the technical field of decoding algorithms for polarization codes, in particular to a polarization code confidence propagation decoding method based on multi-turn bit sets.
  • Polar code is a forward error correction coding method used for signal transmission.
  • the core of the polarization code is through channel polarization processing, and the method is adopted on the coding side to make each sub-channel show different reliability.
  • some channels will tend to be perfect channels with a capacity close to 1 (error-free code). ), another part of the channel tends to be a pure noise channel with a capacity close to 0.
  • Choosing to directly transmit information on a channel with a capacity close to 1 to approach the channel capacity is the only method that can be strictly proven to reach the Shannon limit.
  • the decoding algorithms of polarization codes mainly include SC (Successive Cancellation, serial cancellation) decoding algorithm, maximum likelihood decoding algorithm, linear programming decoding algorithm and belief propagation decoding algorithm.
  • SC decoding algorithm has the lowest complexity, and it has been proved that the polarization code can reach the Shannon limit under the SCL (Successive Cancellation List) decoding algorithm.
  • SCL and SC algorithms have high complexity, high latency and low parallelism.
  • the BP algorithm based on belief propagation has high parallelism, its performance is poor.
  • the prior art BP decoder based on key set bit flipping uses the prior knowledge of unreliable information bits to further reduce the block error rate. By analyzing the bit error rate distribution of the polarization code, the set CS of unreliable bits is identified. In the decoding process, the BFBP-CS algorithm uses cyclic redundancy check to detect block errors. If the traditional BP decoding fails, the received information in CS is set to a preset value, and then BP decoding is used to find the CRC. The code word to be checked.
  • the disadvantage of the above-mentioned prior art BP decoder based on bit flipping of the key set is that the BFBP-CS algorithm has an error leveling phenomenon in the decoder in the high signal-to-noise ratio (SNR) region, and the performance is poor.
  • SNR signal-to-noise ratio
  • the embodiment of the present invention provides a polarization code belief propagation decoding method based on multi-turn bit sets to overcome the problems of the prior art.
  • the present invention adopts the following technical solutions.
  • the decoder outputs The process ends; otherwise, the set of flipped bits is flipped and decoded using the real number matrix to obtain the flipped estimated codeword set u, and the estimated codeword set u is obtained according to the principle of maximum likelihood. And flip the estimated codeword set u to select the optimal estimated codeword, the decoder outputs the optimal estimated codeword , and the process ends.
  • the set of set check conditions S1 and S2, where S1 and S2 contain multiple check conditions for the estimated codeword after decoding include:
  • Pre-set check condition sets S1 and S2.
  • the S1 and S2 contain multiple check conditions for the estimated codeword after decoding. There is no intersection between S1 and S2.
  • the selection principle of S1 and S2 is the lowest missed detection rate.
  • the log-likelihood ratio of the received signal to be decoded is calculated, and the BP algorithm is used to decode the real number matrix storing the log-likelihood ratio to obtain the estimated codeword include:
  • the received signal to be decoded is a vector of length N
  • llr is the signal to be decoded
  • A is the information bit position of the polarization code
  • a c is the freezing bit position of the polarization code
  • L and R are a real matrix with a size of (N,log2(N)+1), which is the belief propagation algorithm of the polarization code
  • the matrix storing the log-likelihood ratio llr in, L and R are initialized with the following formula:
  • R i,0 represents the element at the position (i,0) in the R matrix
  • Li,0 represents the element at the position (i,0) in the L matrix
  • the matrix L and R are initialized, and the BP algorithm is used to decode L and R to obtain the decoded estimated codeword
  • the set of flipped bits is flipped and decoded by using the real number matrix to obtain the flipped estimated codeword set u, and the estimated codeword set u is obtained according to the principle of maximum likelihood.
  • the decoder outputs the optimal estimated codeword, and the process ends, including:
  • Set ⁇ as a sequence of flipped bits, containing n ⁇ sets of flipped bits, namely ⁇ is a sequence of flipped bits, containing n ⁇ sets of flipped bits, namely
  • the process of flipping and decoding BFBP() includes: Is an element in the set of flipped bits ⁇ n, Is a vector of length ⁇ , which represents the position of the flipped bit, Is a vector of length ⁇ , which represents the value corresponding to the flipped bit, let j l be The l th element in It is the (j l ,1)th element in the matrix R. Each element of the flipped bit set ⁇ n is traversed through the function BFBP().
  • G is the generator matrix, the size is (N, N),
  • Decoder output The process ends.
  • the set of flipped bits is flipped and decoded by using the real number matrix to obtain the flipped estimated codeword set u, and the estimated codeword set u is obtained according to the principle of maximum likelihood. And flip the estimated codeword set u to select the optimal estimated codeword, the decoder outputs the optimal estimated codeword , and the process ends, including:
  • the processing process of the flipping decoding function BFBP() includes: Is an element in the flipped bit set ⁇ n, Is a vector of length ⁇ , which represents the position of the flipped bit, Is a vector of length ⁇ , which represents the value corresponding to the flipped bit, Is the (j l ,1)th element in the R matrix.
  • Each element of the flipped bit set ⁇ n is traversed through the function BFBP(). After initializing L and R, use Assign a value to the first column in R and use the BP decoder for decoding. If the output of the BP decoder is If the check condition S1 is met, the traversal is terminated, and the output
  • n ⁇ estimated codewords After flipping and decoding the set of n ⁇ flipped bits in ⁇ , BFBP(), n ⁇ estimated codewords are obtained All estimated codewords form an estimated codeword set u, According to the principle of maximum likelihood, from the set of n ⁇ +1 estimated codewords Select the best estimated codeword, as shown in the following formula:
  • Decoder output The process ends. It can be seen from the technical solutions provided by the above embodiments of the present invention that the various processing procedures in the decoding method of the embodiments of the present invention can be implemented in parallel. Through the present invention, the computational complexity at high signal-to-noise ratios can be less than that of the list. The decoding algorithm is eliminated successively, and the performance is close. The embodiment of the present invention can eliminate the error leveling phenomenon of the (BFBP) decoder.
  • FIG. 1 is a processing flowchart of a polarization code belief propagation decoding method based on a set of multiple flip bits provided by an embodiment of the present invention.
  • the BP (Error Back Propagation) algorithm is a currently published decoding algorithm.
  • the embodiment of the present invention proposes a polarization code belief propagation translation based on a multi-turn bit set and multi-stop mechanism.
  • Code algorithm (BP-MF-MC).
  • I the received signal to be decoded, and is a vector of length N.
  • llr is the signal to be decoded
  • the log-likelihood ratio of It is calculated as a vector of length N.
  • llr i p(y i
  • A is the information bit position of the polarization code
  • a c is the freezing bit position of the polarization code
  • L and R are a real matrix with a size of (N,log2(N)+1), which is the belief propagation algorithm of the polarization code
  • the matrix storing the log-likelihood ratio llr in, L and R are initialized with the following formula:
  • R i,0 represents the element at the position (i,0) in the R matrix
  • Li,0 represents the element at the position (i,0) in the L matrix.
  • BP .,.,.,.
  • CRC Cyclic Redundancy Check
  • S1 and S2 are the pre-check condition set, including the The multiple check conditions can be CRC, LDPC and other check methods. S1 and S2 have no intersection. The selection principle of S1 and S2 is to make the missed detection rate the lowest, S1 can be CRC check, and S2 can be the generator matrix check method.
  • ⁇ is the sequence of flipped bits, containing n ⁇ sets of flipped bits, namely ⁇ is a sequence of flipped bits, containing n ⁇ sets of flipped bits, namely The set of flipped bits can be a key bit sequence set CS of order n, or can be frozen bits Ac , or all information bits A.
  • ⁇ can be ⁇ CS1 ⁇ and ⁇ is ⁇ CS3, A ⁇ .
  • BP-MF-MC polarization code belief propagation decoding method
  • Step S1 first initialize the matrix L and R according to the above formula (1), and then use the traditional BP algorithm to decode L and R to obtain the decoded estimated codeword
  • Step S2 if Meet all the verification conditions in S1 and S2, it can be considered For the correct codeword, the decoder outputs The process ends.
  • Step S2' if All the check conditions in S1 are met, but all check conditions in S2 are not met, and the set of n ⁇ flipped bits in ⁇ is flipped and decoded BFBP().
  • the process of flipping and decoding BFBP() includes: Is an element in the set of flipped bits ⁇ n, Is a vector of length ⁇ , which represents the position of the flipped bit, Is a vector of length ⁇ , which represents the value corresponding to the flipped bit, let j l be The l th element in Is the (j l ,1)th element in the R matrix.
  • G is the generator matrix
  • the size is (N, N).
  • is 2-norm.
  • Decoder output The process ends.
  • Step S2'' if all the check conditions in S1 are not satisfied, the flipping decoding BFBP() is performed on the set of n ⁇ flipped bits in ⁇ .
  • the processing process of the flipping decoding function BFBP() includes: To flip an element in the bit set ⁇ , Is a vector of length ⁇ , which represents the position of the flipped bit, Is a vector of length ⁇ , which represents the value corresponding to the flipped bit, Is the (j l ,1)th element in the R matrix. Use the function BFBP() to traverse each element of the flipped bit set ⁇ . After initializing L and R, use Assign a value to the first column in R, and then use the traditional BP decoder for decoding, if the output of BP decoding If the check condition S1 is met, the traversal is terminated, and the output
  • n ⁇ estimated codewords After flipping and decoding the set of n ⁇ flipped bits in ⁇ , BFBP(), n ⁇ estimated codewords are obtained All estimated codewords form an estimated codeword set u, According to the principle of maximum likelihood, from the set of n ⁇ +1 estimated codewords Select the best estimated codeword, as shown in the following formula:
  • Decoder output The process ends.
  • step S2 step S2' and step S2' can be executed in parallel.
  • Step 1 Use formula (1) to initialize L and R
  • Step 4 Does not meet S2
  • Step 5 For all ⁇ i ⁇
  • Step 7 end for
  • Step 8 else
  • Step 11 for all ⁇ i ⁇
  • Step 13 end for
  • Step 14 end if
  • Step 15 According to formula (2), use the maximum likelihood method to select the best
  • Step 3 Use formula (1) to initialize L and R
  • Step 6 end for
  • Step 11 if Satisfy S
  • Step 15 end for.
  • the various processing procedures in the decoding method of the embodiment of the present invention can be implemented in parallel.
  • the computational complexity at high signal-to-noise ratio can be less than that of the list successive elimination decoding algorithm, and the performance is close.
  • the embodiment of the present invention can eliminate the error leveling phenomenon of the (BFBP) decoder, is a BP decoder with similar performance to the CRC-assisted SCL decoder (CA-SCL), and has high parallelism.
  • the present invention can be implemented by means of software plus a necessary general hardware platform.
  • the technical solution of the present invention essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product can be stored in a storage medium, such as ROM/RAM, magnetic disk , CD-ROM, etc., including a number of instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute the methods described in the various embodiments or some parts of the embodiments of the present invention.

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Abstract

一种基于多翻转比特集合的极化码置信传播译码方法。该方法包括：设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，计算出待译码的接收信号的对数似然比，使用BP算法对存储所述对数似然比的实数矩阵进行译码，得到估计码字 û1；判断 û1是否满足S1及S2中的所有校验条件，如果是，则确定 û1为正确码字，译码器输出 û1，流程结束；否则，利用实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从估计码字 û1和翻转估计码字集合u中选出最优估计码字，流程结束。所述方法中的各种处理流程可以并行实现，在高信噪比时的计算复杂度可以小于列表逐次消除译码算法，性能接近。

Description

基于多翻转比特集合的极化码置信传播译码方法 技术领域
本发明涉及极化码的译码算法技术领域，尤其涉及一种基于多翻转比特集合的极化码置信传播译码方法。
背景技术
极化码(Polar code)是一种前向错误更正编码方式，用于讯号传输。极化码的核心是通过信道极化处理，在编码侧采用方法使各个子信道呈现出不同的可靠性，当码长持续增加时，部分信道将趋向于容量近于1的完美信道(无误码)，另一部分信道趋向于容量接近于0的纯噪声信道，选择在容量接近于1的信道上直接传输信息以逼近信道容量，是目前唯一能够被严格证明可以达到香农极限的方法。
极化码一经提出，立刻受到了众多学者的关注，成为信息领域的研究热点。在信道编码方案中，极化码的编译码复杂度低，并且已经被严格证明能达到香农极限，因此，极化码具有极高的研究意义。在近些年的研究中，极化码的译码算法主要有SC(Successive Cancellation，串行抵消)译码算法、最大似然译码算法、线性规划译码算法及置信传播译码算法。其中，SC译码算法的复杂度最低，且被证明极化码在SCL(Successive Cancellation List，串行抵消列表))译码算法下可以达到香农极限。但SCL及SC算法复杂度高，且延迟大，并行度低。基于置信传播的BP算法虽然并行高，但是性能较差。
现有技术中的基于关键集的比特翻转的BP译码器(BFBP-CS)是利用了不可靠信息位的先验知识，来进一步降低误块率。通过分析极化码的误比特率的分布，识别出不可靠比特的集合CS。在译码的过程中，BFBP-CS算法使用循环冗余校验来检测块错误，若传统BP译码失败，则将CS中的接收信息设置为预设值，然后采用BP译码寻找通过CRC校验的码字。
上述现有技术中的基于关键集的比特翻转的BP译码器的缺点为：BFBP-CS算法在解码器在高信噪比(SNR)区域具有出误差平层现象，性能较差。
发明内容
本发明的实施例提供了一种基于多翻转比特集合的极化码置信传播译码方法，以克服现有技术的问题。
为了实现上述目的，本发明采取了如下技术方案。
一种基于多翻转比特集合的极化码置信传播译码方法，设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，所述方法包括：
计算出待译码的接收信号的对数似然比，使用BP算法对存储所述对数似然比的实数矩阵进行译码，得到估计码字
Figure PCTCN2020098756-appb-000001
判断
Figure PCTCN2020098756-appb-000002
是否满足S1及S2中的所有校验条件，如果是，则确定
Figure PCTCN2020098756-appb-000003
为正确码字，译码器输出
Figure PCTCN2020098756-appb-000004
流程结束；否则，利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
Figure PCTCN2020098756-appb-000005
和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字 ，流程结束。
优选地，所述的设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，包括：
预先设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的 多个校验条件，S1与S2无交集，S1和S2的选取原则为漏检率最低。
优选地，所述的计算出待译码的接收信号的对数似然比，使用BP算法对存储所述对数似然比的实数矩阵进行译码，得到估计码字
Figure PCTCN2020098756-appb-000006
包括：
设
Figure PCTCN2020098756-appb-000007
为待译码的接收信号，为一长度为N的一个向量，llr为待译码信号
Figure PCTCN2020098756-appb-000008
的对数似然比，为一长度为N的一个向量，即llr i＝p(y i|0)/p(y i|1)，其中，llr i为llr中第i个元素，y i为
Figure PCTCN2020098756-appb-000009
中第i个元素，p(y i|0)为输入为0时的条件概率，p(y i|1)为输入为1时的条件概率；
A是极化码的信息比特位置，A c是极化码的冻结比特位置，L与R为一实数矩阵，其大小为(N,log2(N)+1)，是极化码置信传播算法中存储对数似然比llr的矩阵，L和R采用如下公式初始化：
Figure PCTCN2020098756-appb-000010
其中，R i，0表示R矩阵中位置为(i,0)的元素，L i，0表示L矩阵中位置为(i,0)的元素；
按照上述公式(1)对矩阵L及R进行初始化，使用BP算法对L及R进行译码，得到译码的估计码字
Figure PCTCN2020098756-appb-000011
优选地，所述的利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
Figure PCTCN2020098756-appb-000012
和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字，流程结束，包括：
设定Φ为翻转比特序列，含有n φ个翻转比特集合，即
Figure PCTCN2020098756-appb-000013
Ψ为翻转比特序列，含有n ψ个翻转比特集合，即
Figure PCTCN2020098756-appb-000014
如果估计码字
Figure PCTCN2020098756-appb-000015
满足S1中的所有校验条件，但不满足S2中的所有校验条 件，对Φ中n φ个翻转比特集合进行翻转译码BFBP()，该翻转译码BFBP()的处理过程包括：设
Figure PCTCN2020098756-appb-000016
为翻转比特集合φ n中的一个元素，
Figure PCTCN2020098756-appb-000017
为长度ω的向量，代表了翻转比特的位置，
Figure PCTCN2020098756-appb-000018
为长度ω的向量，代表了翻转比特对应的值，设j l为
Figure PCTCN2020098756-appb-000019
中第l个元素，
Figure PCTCN2020098756-appb-000020
是矩阵R中第(j l,1)个元素，通过函数BFBP()对翻转比特集合φ n的每个元素进行遍历，在对L及R初始化后，使用
Figure PCTCN2020098756-appb-000021
对矩阵R中第1列进行赋值，使用BP译码器对赋值后的矩阵R进行译码，如果BP译码的输出
Figure PCTCN2020098756-appb-000022
满足校验条件S1，则遍历终止，输出
Figure PCTCN2020098756-appb-000023
对Φ中n φ个翻转比特集合进行翻转译码BFBP()后得到n φ个估计码字
Figure PCTCN2020098756-appb-000024
所有估计码字组成估计码字集合u，
Figure PCTCN2020098756-appb-000025
按照最大似然原则，从n φ+1个估计码字集合
Figure PCTCN2020098756-appb-000026
选出最优估计码字，如下式所示：
Figure PCTCN2020098756-appb-000027
其中，G为生成矩阵，大小为(N,N)，||·||为2-范数；
译码器输出
Figure PCTCN2020098756-appb-000028
流程结束。
优选地，所述的利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
Figure PCTCN2020098756-appb-000029
和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字 ，流程结束，包括：
如果
Figure PCTCN2020098756-appb-000030
不满足S1中的所有校验条件，对Ψ中n ψ个翻转比特集合进行翻转译码BFBP()，该翻转译码函数BFBP()的处理过程包括：设
Figure PCTCN2020098756-appb-000031
为翻转比特集合ψ n，中的一个元素，
Figure PCTCN2020098756-appb-000032
为长度ω的向量，代表了翻转比特的位置，
Figure PCTCN2020098756-appb-000033
为长度ω的向量，代表了翻转比特对应的值，
Figure PCTCN2020098756-appb-000034
是R矩阵中第(j l,1)个元素，通过函数BFBP()对翻转比特集合ψ n，的每个元素进行遍历，在对L及R初始化后，使用
Figure PCTCN2020098756-appb-000035
对R中第1列进行赋值，使用BP译码器进行译码，如果BP译码的输出
Figure PCTCN2020098756-appb-000036
满足校验条件S1，则遍历终止，输出
Figure PCTCN2020098756-appb-000037
对Ψ中n φ个翻转比特集合进行翻转译码BFBP()后，得到n ψ个估计码字
Figure PCTCN2020098756-appb-000038
所有估计码字组成估计码字集合u，
Figure PCTCN2020098756-appb-000039
按照最大似然原则，从n ψ+1个估计码字集合
Figure PCTCN2020098756-appb-000040
选出最优估计码字，如下式所示：
Figure PCTCN2020098756-appb-000041
译码器输出
Figure PCTCN2020098756-appb-000042
流程结束。由上述本发明的实施例提供的技术方案可以看出，本发明实施例的译码方法中的各种处理流程可以并行实现，通过本发明，在高信噪比时的计算复杂度可以小于列表逐次消除译码算法，性能接近。本发明实施例可以消除(BFBP)解码器的误码平层现象。
本发明附加的方面和优点将在下面的描述中部分给出，这些将从下面的描述中变得明显，或通过本发明的实践了解到。
附图说明
为了更清楚地说明本发明实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的一种基于多翻转比特集合的极化码置信传播译码方法的处理流程图。
具体实施方式
下面详细描述本发明的实施方式，所述实施方式的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施方式是示例性的，仅用于解释本发明，而不能解释为对本发明的限制。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式 “一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本发明的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解，当我们称元件被“连接”或“耦接”到另一元件时，它可以直接连接或耦接到其他元件，或者也可以存在中间元件。此外，这里使用的“连接”或“耦接”可以包括无线连接或耦接。这里使用的措辞“和/或”包括一个或更多个相关联的列出项的任一单元和全部组合。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)具有与本发明所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像这里一样定义，不会用理想化或过于正式的含义来解释。
为便于对本发明实施例的理解，下面将结合附图以几个具体实施例为例做进一步的解释说明，且各个实施例并不构成对本发明实施例的限定。
BP(Error Back Propagation,误差反向传播)算法是目前一种已经公开的译码算法，本发明实施例基于BP算法，提出了一种基于多翻转比特集合多停止机制的极化码置信传播译码算法(BP-MF-MC)。在该算法中，假定，
Figure PCTCN2020098756-appb-000043
为待译码的接收信号，为一长度为N的一个向量。llr为待译码信号
Figure PCTCN2020098756-appb-000044
的对数似然比，由
Figure PCTCN2020098756-appb-000045
计算出，为一长度为N的一个向量。即llr i＝p(y i|0)/p(y i|1)，其中，llr i为llr中第i个元素，y i为
Figure PCTCN2020098756-appb-000046
中第i个元素，p(y i|0)为输入为0时的条件概率，p(y i|1)为输入为1时的条件概率。
A是极化码的信息比特位置，A c是极化码的冻结比特位置，L与R为一实数矩阵，其大小为(N,log2(N)+1)，是极化码置信传播算法中存储对数似然比llr的矩阵，L和R采用如下公式初始化：
Figure PCTCN2020098756-appb-000047
其中，R i，0表示R矩阵中位置为(i,0)的元素，L i，0表示L矩阵中位置为(i,0)的元素。
Figure PCTCN2020098756-appb-000048
为本发明实施例的译码器的输出比特，长度为N。BP(.,.,.,.)为使用CRC(Cyclic Redundancy Check，循环冗余校验)校验作为停止条件的传统BP算法，其输出为
Figure PCTCN2020098756-appb-000049
长度为N，BFBP()参见算法2。S1，S2为预先校验条件集合，包含对
Figure PCTCN2020098756-appb-000050
的多个校验条件，可以为CRC，LDPC等校验方法。S1与S2无交集。S1和S2的选取原则是让漏检率最低，S1可以为CRC校验，S2可以为生成矩阵校验法。
Φ为翻转比特序列，含有n φ个翻转比特集合，即
Figure PCTCN2020098756-appb-000051
Ψ为翻转比特序列，含有n ψ个翻转比特集合，即
Figure PCTCN2020098756-appb-000052
翻转比特集合可以为n阶关键比特序列集合CS，也可以是冻结比特A c，或全部信息比特A。例如，Φ可为{CS1}，Ψ为{CS3，A}。
本发明实施例提出的基于多翻转比特集合的极化码置信传播译码方法(BP-MF-MC)的处理流程如图1所示，包括如下的处理步骤：
步骤S1、首先按照上述公式(1)对矩阵L及R进行初始化，然后使用传统的BP算法对L及R进行译码，得到译码的估计码字
Figure PCTCN2020098756-appb-000053
步骤S2、如果
Figure PCTCN2020098756-appb-000054
满足S1及S2中的所有校验条件，则可以认为
Figure PCTCN2020098756-appb-000055
为正确码字，译码器输出
Figure PCTCN2020098756-appb-000056
流程结束。
步骤S2‘、如果
Figure PCTCN2020098756-appb-000057
满足S1中的所有校验条件，但不满足S2中的所有校验条件，对Φ中n φ个翻转比特集合进行翻转译码BFBP()，该翻转译码BFBP()的处理过程包括：设
Figure PCTCN2020098756-appb-000058
为翻转比特集合φ n中的一个元素，
Figure PCTCN2020098756-appb-000059
为长度ω的向 量，代表了翻转比特的位置，
Figure PCTCN2020098756-appb-000060
为长度ω的向量，代表了翻转比特对应的值，设j l为
Figure PCTCN2020098756-appb-000061
中第l个元素，
Figure PCTCN2020098756-appb-000062
是R矩阵中第(j l,1)个元素。通过函数BFBP()对翻转比特集合φ n的每个元素进行遍历，在对L及R初始化后，使用
Figure PCTCN2020098756-appb-000063
对矩阵R中第1列进行赋值，使用传统的BP译码器对赋值后的矩阵R进行译码，如果BP译码的输出
Figure PCTCN2020098756-appb-000064
满足校验条件S1，则遍历终止，输出
Figure PCTCN2020098756-appb-000065
对Φ中n φ个翻转比特集合进行翻转译码BFBP()后得到n φ个估计码字
Figure PCTCN2020098756-appb-000066
所有估计码字组成估计码字集合u，
Figure PCTCN2020098756-appb-000067
按照最大似然原则，从n φ+1个估计码字集合
Figure PCTCN2020098756-appb-000068
选出最优估计码字，如下式所示：
Figure PCTCN2020098756-appb-000069
其中，G为生成矩阵，大小为(N,N)。||·||为2-范数。
译码器输出
Figure PCTCN2020098756-appb-000070
流程结束。
步骤S2’‘、如果
Figure PCTCN2020098756-appb-000071
不满足S1中的所有校验条件，对Ψ中n ψ个翻转比特集合进行翻转译码BFBP()，该翻转译码函数BFBP()的处理过程包括：设
Figure PCTCN2020098756-appb-000072
为翻转比特集合Ψ中的一个元素，
Figure PCTCN2020098756-appb-000073
为长度ω的向量，代表了翻转比特的位置，
Figure PCTCN2020098756-appb-000074
为长度ω的向量，代表了翻转比特对应的值，
Figure PCTCN2020098756-appb-000075
是R矩阵中第(j l,1)个元素。通过函数BFBP()对翻转比特集合Ψ的每个元素进行遍历，在对L及R初始化后，使用
Figure PCTCN2020098756-appb-000076
对R中第1列进行赋值，然后使用传统的BP译码器进行译码，如果BP译码的输出
Figure PCTCN2020098756-appb-000077
满足校验条件S1，则遍历终止，输出
Figure PCTCN2020098756-appb-000078
对Ψ中n φ个翻转比特集合进行翻转译码BFBP()后，得到n ψ个估计码字
Figure PCTCN2020098756-appb-000079
所有估计码字组成估计码字集合u，
Figure PCTCN2020098756-appb-000080
按照最大似然原则，从n ψ+1个估计码字集合
Figure PCTCN2020098756-appb-000081
选出最优估计码字，如下式所示：
Figure PCTCN2020098756-appb-000082
译码器输出
Figure PCTCN2020098756-appb-000083
流程结束。
上述步骤S2、步骤S2‘和步骤S2’‘可并列执行。
算法1 BP-MF-MC的代码流程如下：
输入：llr，A,Φ,Ψ,S1，S2
输出：
Figure PCTCN2020098756-appb-000084
步骤1:使用公式(1)初始化L及R
步骤2:
Figure PCTCN2020098756-appb-000085
步骤3:If
Figure PCTCN2020098756-appb-000086
满足S1
步骤4:
Figure PCTCN2020098756-appb-000087
不满足S2
步骤5:For all Φi∈Φ
步骤6:Ui＝BFBP(llr,A,Φi,S1)
步骤7:end for
步骤8:else
步骤9:return
Figure PCTCN2020098756-appb-000088
步骤10:else
步骤11:for all Ψi∈Ψ
步骤12:Ui＝BFBP(llr,A,Ψi,S1)
步骤13:end for
步骤14:end if
步骤15:据式(2)采用最大似然法从选出最好的
Figure PCTCN2020098756-appb-000089
算法2 函数BFBP的的代码流程如下：
输入：llr，A,Ω,S
输出：
Figure PCTCN2020098756-appb-000090
步骤1:i＝1
步骤2:for
Figure PCTCN2020098756-appb-000091
do
步骤3:使用公式(1)初始化L及R
步骤4:for l＝1 to ω do
步骤5:
Figure PCTCN2020098756-appb-000092
步骤6:end for
步骤7:
Figure PCTCN2020098756-appb-000093
步骤8:if i＝＝1
步骤9:
Figure PCTCN2020098756-appb-000094
步骤10:end
步骤11:if
Figure PCTCN2020098756-appb-000095
满足S
步骤12:
Figure PCTCN2020098756-appb-000096
步骤13:end
步骤14:i++
步骤15:end for。
综上所述，本发明实施例的译码方法中的各种处理流程可以并行实现，通过本发明，在高信噪比时的计算复杂度可以小于列表逐次消除译码算法，性能接近。本发明实施例可以消除(BFBP)解码器的误码平层现象，是一种与CRC辅助的SCL解码器(CA-SCL)性能相近的BP解码器，且并行度高。
本领域普通技术人员可以理解：附图只是一个实施例的示意图，附图中的模块或流程并不一定是实施本发明所必须的。
通过以上的实施方式的描述可知，本领域的技术人员可以清楚地了解到本发明可借助软件加必需的通用硬件平台的方式来实现。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例或者实施例的某些部分所 述的方法。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于装置或系统实施例而言，由于其基本相似于方法实施例，所以描述得比较简单，相关之处参见方法实施例的部分说明即可。以上所描述的装置及系统实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
以上所述，仅为本发明较佳的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权利要求的保护范围为准。

Claims (5)

  1. 一种基于多翻转比特集合的极化码置信传播译码方法，其特征在于，设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，所述方法包括：
    计算出待译码的接收信号的对数似然比，使用BP算法对存储所述对数似然比的实数矩阵进行译码，得到估计码字
    Figure PCTCN2020098756-appb-100001
    判断
    Figure PCTCN2020098756-appb-100002
    是否满足S1及S2中的所有校验条件，如果是，则确定
    Figure PCTCN2020098756-appb-100003
    为正确码字，译码器输出
    Figure PCTCN2020098756-appb-100004
    流程结束；否则，利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
    Figure PCTCN2020098756-appb-100005
    和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字，流程结束。
  2. 根据权利要求1所述的方法，其特征在于，所述的设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，包括：
    预先设定校验条件集合S1、S2，该S1、S2中包含对译码后的估计码字的多个校验条件，S1与S2无交集，S1和S2的选取原则为漏检率最低。
  3. 根据权利要求1所述的方法，其特征在于，所述的计算出待译码的接收信号的对数似然比，使用BP算法对存储所述对数似然比的实数矩阵进行译码，得到估计码字
    Figure PCTCN2020098756-appb-100006
    包括：
    设
    Figure PCTCN2020098756-appb-100007
    为待译码的接收信号，为一长度为N的一个向量，llr为待译码信号
    Figure PCTCN2020098756-appb-100008
    的对数似然比，为一长度为N的一个向量，即llr i＝p(y i|0)/p(y i|1)，其中，llr i为llr中第i个元素，y i为
    Figure PCTCN2020098756-appb-100009
    中第i个元素，p(y i|0)为输入为0时的条件概率，p(y i|1)为输入为1时的条件概率；
    A是极化码的信息比特位置，A c是极化码的冻结比特位置，L与R为一实 数矩阵，其大小为(N,log2(N)+1)，是极化码置信传播算法中存储对数似然比llr的矩阵，L和R采用如下公式初始化：
    Figure PCTCN2020098756-appb-100010
    其中，R i，0表示R矩阵中位置为(i,0)的元素，L i，0表示L矩阵中位置为(i,0)的元素；
    按照上述公式(1)对矩阵L及R进行初始化，使用BP算法对L及R进行译码，得到译码的估计码字
    Figure PCTCN2020098756-appb-100011
  4. 根据权利要求3所述的方法，其特征在于，所述的利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
    Figure PCTCN2020098756-appb-100012
    和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字，流程结束，包括：
    设定Φ为翻转比特序列，含有n φ个翻转比特集合，即
    Figure PCTCN2020098756-appb-100013
    Ψ为翻转比特序列，含有n ψ个翻转比特集合，即
    Figure PCTCN2020098756-appb-100014
    如果估计码字
    Figure PCTCN2020098756-appb-100015
    满足S1中的所有校验条件，但不满足S2中的所有校验条件，对Φ中n φ个翻转比特集合进行翻转译码BFBP()，该翻转译码BFBP()的处理过程包括：设
    Figure PCTCN2020098756-appb-100016
    为翻转比特集合φ n中的一个元素，
    Figure PCTCN2020098756-appb-100017
    为长度ω的向量，代表了翻转比特的位置，
    Figure PCTCN2020098756-appb-100018
    为长度ω的向量，代表了翻转比特对应的值，设j l为
    Figure PCTCN2020098756-appb-100019
    中第l个元素，
    Figure PCTCN2020098756-appb-100020
    是矩阵R中第(j l,1)个元素，通过函数BFBP()对翻转比特集合φ n的每个元素进行遍历，在对L及R初始化后，使用
    Figure PCTCN2020098756-appb-100021
    对矩阵R中第1列进行赋值，使用BP译码器对赋值后的矩阵R进行译码，如果BP译码的输出
    Figure PCTCN2020098756-appb-100022
    满足校验条件S1，则遍历终止，输出
    Figure PCTCN2020098756-appb-100023
    对Φ中n φ个翻转比特集合进行翻转译码BFBP()后得到n φ个估计码字
    Figure PCTCN2020098756-appb-100024
    所有估计码字组成估计码字集合u，
    Figure PCTCN2020098756-appb-100025
    按照最大似然原 则，从n φ+1个估计码字集合
    Figure PCTCN2020098756-appb-100026
    选出最优估计码字，如下式所示：
    Figure PCTCN2020098756-appb-100027
    其中，G为生成矩阵，大小为(N,N)，||·||为2-范数；
    译码器输出
    Figure PCTCN2020098756-appb-100028
    流程结束。
  5. 根据权利要求3所述的方法，其特征在于，所述的利用所述实数矩阵对设定的翻转比特集合进行翻转译码后得到翻转估计码字集合u，按照最大似然原则，从所述估计码字
    Figure PCTCN2020098756-appb-100029
    和翻转估计码字集合u中选出最优估计码字，译码器输出最优估计码字，流程结束，包括：
    如果
    Figure PCTCN2020098756-appb-100030
    不满足S1中的所有校验条件，对Ψ中n ψ个翻转比特集合进行翻转译码BFBP()，该翻转译码函数BFBP()的处理过程包括：设
    Figure PCTCN2020098756-appb-100031
    为翻转比特集合ψ n，中的一个元素，
    Figure PCTCN2020098756-appb-100032
    为长度ω的向量，代表了翻转比特的位置，
    Figure PCTCN2020098756-appb-100033
    为长度ω的向量，代表了翻转比特对应的值，
    Figure PCTCN2020098756-appb-100034
    是R矩阵中第(j l,1)个元素，通过函数BFBP()对翻转比特集合ψ n，的每个元素进行遍历，在对L及R初始化后，使用
    Figure PCTCN2020098756-appb-100035
    对R中第1列进行赋值，使用BP译码器进行译码，如果BP译码的输出
    Figure PCTCN2020098756-appb-100036
    满足校验条件S1，则遍历终止，输出
    Figure PCTCN2020098756-appb-100037
    对Ψ中n φ个翻转比特集合进行翻转译码BFBP()后，得到n ψ个估计码字
    Figure PCTCN2020098756-appb-100038
    所有估计码字组成估计码字集合u，
    Figure PCTCN2020098756-appb-100039
    按照最大似然原则，从n ψ+1个估计码字集合
    Figure PCTCN2020098756-appb-100040
    选出最优估计码字，如下式所示：
    Figure PCTCN2020098756-appb-100041
    译码器输出
    Figure PCTCN2020098756-appb-100042
    流程结束。
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114157309A (zh) * 2021-12-23 2022-03-08 华中科技大学 极化码译码方法、装置及系统
CN114421975A (zh) * 2022-01-18 2022-04-29 重庆邮电大学 一种基于翻转集的极化码sclf译码方法
CN116232340A (zh) * 2022-12-15 2023-06-06 中国人民解放军战略支援部队信息工程大学 一种卫星通信信号的稀疏校验矩阵参数估计方法及装置

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111446973B (zh) * 2020-04-17 2022-03-25 北京交通大学 基于多翻转比特集合的极化码置信传播译码方法
CN113242045A (zh) * 2021-04-01 2021-08-10 湖南矩阵电子科技有限公司 一种极化码的高效译码方法、译码装置及计算机可读存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190089374A1 (en) * 2016-03-30 2019-03-21 Silicon Motion Inc. Bit flipping algorithm for providing soft information during hard decision hard decoding
CN110380819A (zh) * 2019-07-03 2019-10-25 深圳大学 一种基于llr的分段翻转极化码译码方法和智能终端
CN110798228A (zh) * 2019-10-29 2020-02-14 南京宁麒智能计算芯片研究院有限公司 一种基于深度学习的极化码翻转译码方法及系统
CN110995279A (zh) * 2019-12-17 2020-04-10 重庆邮电大学 一种极化码联合scf球形列表翻转译码方法
CN110995278A (zh) * 2019-12-16 2020-04-10 重庆邮电大学 一种改进极性码串行消除列表比特翻转译码方法及系统

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8677227B2 (en) * 2010-08-25 2014-03-18 Royal Institution for the Advancement of Learning / McGill University Method and system for decoding
US9917675B2 (en) * 2016-06-01 2018-03-13 Qualcomm Incorporated Enhanced polar code constructions by strategic placement of CRC bits
CN107241106B (zh) * 2017-05-24 2020-07-14 东南大学 基于深度学习的极化码译码算法
CN109842418B (zh) * 2018-11-27 2022-12-27 东南大学 一种基于比特翻转的极化码置信传播译码方法
CN109660264B (zh) * 2018-12-03 2023-05-05 中国人民解放军陆军工程大学 高性能极化码译码算法
CN110278002B (zh) * 2019-06-19 2023-01-17 东南大学 基于比特翻转的极化码置信传播列表译码方法
CN110492974B (zh) * 2019-08-19 2020-08-07 北京邮电大学 一种并行的极化码译码方法及装置
CN110830167A (zh) * 2019-10-31 2020-02-21 中国计量大学 基于多比特翻转的极化码Fast-SSC译码算法
CN111010196B (zh) * 2019-12-31 2021-09-03 北京航空航天大学 一种极化码BP List译码方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190089374A1 (en) * 2016-03-30 2019-03-21 Silicon Motion Inc. Bit flipping algorithm for providing soft information during hard decision hard decoding
CN110380819A (zh) * 2019-07-03 2019-10-25 深圳大学 一种基于llr的分段翻转极化码译码方法和智能终端
CN110798228A (zh) * 2019-10-29 2020-02-14 南京宁麒智能计算芯片研究院有限公司 一种基于深度学习的极化码翻转译码方法及系统
CN110995278A (zh) * 2019-12-16 2020-04-10 重庆邮电大学 一种改进极性码串行消除列表比特翻转译码方法及系统
CN110995279A (zh) * 2019-12-17 2020-04-10 重庆邮电大学 一种极化码联合scf球形列表翻转译码方法

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114157309A (zh) * 2021-12-23 2022-03-08 华中科技大学 极化码译码方法、装置及系统
CN114421975A (zh) * 2022-01-18 2022-04-29 重庆邮电大学 一种基于翻转集的极化码sclf译码方法
CN116232340A (zh) * 2022-12-15 2023-06-06 中国人民解放军战略支援部队信息工程大学 一种卫星通信信号的稀疏校验矩阵参数估计方法及装置
CN116232340B (zh) * 2022-12-15 2023-10-13 中国人民解放军战略支援部队信息工程大学 一种卫星通信信号的稀疏校验矩阵参数估计方法及装置

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