CN109951189B - Quasi-cyclic structure multi-element LDPC code construction method based on prime number product - Google Patents
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Abstract
Description
技术领域technical field
本发明涉及数字通信和数字存储的研究领域,特别涉及一种基于素数乘积的准循环结构多元LDPC码构造方法。The invention relates to the research field of digital communication and digital storage, in particular to a method for constructing a quasi-circular structure multivariate LDPC code based on the product of prime numbers.
背景技术Background technique
近年来涌现出以自动化工程、车联网为代表的新型无线通信场景,它们对现有通信系统的时延和可靠性均提出挑战。为满足新型应用的的时延和可靠性要求,须在物理层装配面向短数据包的高可靠信道编码技术。目前可选的面向短数据包通信的信道编码技术包括咬尾卷积码、极化码和多元低密度校验码。相比于咬尾卷积码和卷积码,多元低密度校验码具有更低的错误平层。同时多元低密度校验码的编译码器的可并行度更高。因此,多元低密度校验码更加适用于面向短数据包的高可靠通信。In recent years, new wireless communication scenarios represented by automation engineering and Internet of Vehicles have emerged, which pose challenges to the delay and reliability of existing communication systems. In order to meet the delay and reliability requirements of new applications, the physical layer must be equipped with highly reliable channel coding technology for short data packets. Currently available channel coding techniques for short-packet communication include tail-biting convolutional codes, polar codes, and multivariate low-density check codes. Compared with tail-biting convolutional codes and convolutional codes, multivariate LDPC codes have a lower error floor. At the same time, the multivariate LDPC codec has a higher degree of parallelism. Therefore, multivariate low-density check codes are more suitable for high-reliability communication oriented to short data packets.
Gallager最早于上世纪六十年代提出多元低密度校验码,即多元LDPC码。多元LDPC码的研究热潮则始于上世纪末。现有的多元LDPC码的构造方法主要有两类:基于渐进边增长算法的随机构造方法和基于有限域等结构的代数构造方法。随机构造方法可构造任意码长、任意码率的多元LDPC码。代数构造方法可用于构造结构化的多元LDPC码,但代数方法可构造的码严重受限。基于有限域等代数结构可构造速率兼容的多元LDPC码,一种结构化的多元速率兼容LDPC码构造方法,然而该方法受限于代数结构的特性。Gallager first proposed multivariate low-density check codes, namely multivariate LDPC codes, in the 1960s. The research boom of multivariate LDPC codes began at the end of last century. There are two main types of construction methods for existing multivariate LDPC codes: random construction methods based on progressive edge growth algorithm and algebraic construction methods based on finite fields and other structures. The random construction method can construct multi-element LDPC codes with any code length and any code rate. Algebraic construction methods can be used to construct structured multivariate LDPC codes, but the codes that can be constructed by algebraic methods are severely limited. Based on algebraic structures such as finite fields, rate-compatible multivariate LDPC codes can be constructed, which is a structured method for constructing multivariate rate-compatible LDPC codes. However, this method is limited by the characteristics of algebraic structures.
随机构造的多元LDPC码结构性差,硬件实现复杂度高,不具实用性。代数构造方法的灵活性较低。由于存在大量度数较低的变量结点,基于RA结构的多元LDPC码的错误平层较高。另外,基于RA的多元LDPC码一般是非规则的。Randomly constructed multivariate LDPC codes have poor structure, high hardware implementation complexity, and impracticality. Algebraic construction methods are less flexible. Due to the existence of a large number of variable nodes with low degrees, the error floor of multivariate LDPC codes based on RA structure is relatively high. In addition, RA-based multivariate LDPC codes are generally irregular.
发明内容Contents of the invention
本发明的目的在于克服现有技术的缺点与不足,提供一种基于素数乘积的结构化多元LDPC码构造方法,该方法具有构造灵活性高、构造流程简单等优点,所得的多元LDPC码的环长至少为6。一方面,相对于基于渐进边增长的随机构造方法和基于RA的构造方法,本发明所构造的多元LDPC码具有规则的结构,便于硬件实现。另一方面,相对于现有的结构化多元LDPC码,本发明提出的构造方法不基于任何代数结构,因此灵活性更高。The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and provide a structured multivariate LDPC code construction method based on the product of prime numbers. The method has the advantages of high structural flexibility and simple construction process. be at least 6 long. On the one hand, compared with the random construction method based on progressive edge growth and the construction method based on RA, the multivariate LDPC code constructed by the present invention has a regular structure, which is convenient for hardware implementation. On the other hand, compared with the existing structured multivariate LDPC codes, the construction method proposed by the present invention is not based on any algebraic structure, so the flexibility is higher.
本发明的目的通过以下的技术方案实现:The purpose of the present invention is achieved through the following technical solutions:
一种基于素数乘积的准循环结构多元LDPC码构造方法,包括以下步骤:A method for constructing a quasi-cyclic structure multivariate LDPC code based on the product of prime numbers, comprising the following steps:
给定一个有限域Fq,其中q=2m,1≤m;选定s个素数p1,p2,…,ps,其中s≥2;选定λ和ρ,其中2≤λ≤ρ≤p1;给定λ个非负整数r0,r1,…,rλ-1和ρ个非负整数c0,c1,…,cρ-1;给定一个二元矩阵M,其元素取值只能为“0”或“1”;Given a finite field F q , where q=2 m , 1≤m; select s prime numbers p 1 , p 2 ,…,p s , where s≥2; select λ and ρ, where 2≤λ≤ ρ≤p 1 ; given λ non-negative integers r 0 , r 1 ,…,r λ-1 and ρ non-negative integers c 0 , c 1 ,…,c ρ-1 ; given a binary matrix M , whose elements can only take values of "0" or "1";
对于生成长度为p的行向量ei,j,0,其中,p=p1×p2×…×ps,i=0,1,…,λ-1和j=0,1,…,ρ-1,从0开始计数,行向量ei,j,0的第f(i,j)个分量的取值为Mi,j,其他分量的取值为“0”,其中f(i,j)=ri×cj,Mi,j代表矩阵M的第i行、第j列的元素;For generating a row vector e i,j,0 of length p, where, p=p 1 ×p 2 ×…×p s , i=0,1,…,λ-1 and j=0,1,…, ρ-1, counting from 0, the row vector e i,j, the value of the f(i,j)th component of 0 is M i,j , and the value of other components is "0", where f(i ,j)=r i ×c j , M i,j represents the elements of the i-th row and j-th column of the matrix M;
行向量ei,j,k的第0个分量为行向量ei,j,k-1的第p-1个分量,其中k=1,2,…,p-1,而行向量ei,j,k的第s个分量为行向量ei,j,k-1的第s-1个分量,其中s=1,2,…,p-1;The 0th component of the row vector e i,j,k is the p-1th component of the row vector e i,j,k-1 , where k=1,2,...,p-1, and the row vector e i The sth component of ,j,k is the s-1th component of the row vector e i,j,k-1 , where s=1,2,...,p-1;
构造维度为p×p的循环置换矩阵:Construct a circular permutation matrix of dimension p×p:
其中,i=0,1,…,λ-1,j=0,1,…,ρ-1,p为行向量的长度;Wherein, i=0,1,...,λ-1, j=0,1,...,ρ-1, p is the length of the row vector;
构造维度为p×ρp的矩阵:Construct a matrix of dimension p×ρp:
其中,ρ表示第二矩阵Λi中包含的第一矩阵的个数;Wherein, ρ represents the number of the first matrix that comprises in the second matrix Λ i ;
基于矩阵Λ1,Λ2,…,Λλ-1,生成维度为λp×ρp的矩阵:Based on the matrix Λ 1 , Λ 2 ,…,Λ λ-1 , generate a matrix with dimension λp×ρp:
其中,λ表示第三矩阵Λ中包含的第二矩阵的个数;Wherein, λ represents the number of the second matrix contained in the third matrix Λ;
将矩阵Λ中的“1”替换为有限域Fq中的非零元,得到多元LDPC码的维度为λp×ρp的校验矩阵H,校验矩阵H的零空间定义一个有限域Fq上的多元LDPC码。Replace the "1" in the matrix Λ with the non-zero elements in the finite field F q to obtain the parity check matrix H whose dimension is λp×ρp of the multivariate LDPC code, and the null space of the parity check matrix H defines a finite field F q multivariate LDPC codes.
进一步地,所述替换,替换过程按照如下三种方式进行:Further, the replacement, the replacement process is carried out in the following three ways:
对于矩阵Λ的每一个“1”,随机产生一个有限域的非零元进行替换;For each "1" of the matrix Λ, a non-zero element of a finite field is randomly generated for replacement;
对于矩阵Λi,j中的所有“1”采用同一个随机产生的有限域的非零元进行替换;For all "1" in the matrix Λ i,j, the non-zero elements of the same randomly generated finite field are used to replace;
对于矩阵Λ的同一列的所有“1”采用同一个随机产生的有限域的非零元进行替换;For all "1" in the same column of the matrix Λ, the non-zero elements of the same randomly generated finite field are used to replace;
进一步地,所述素数,满足3≤p1≤p2≤…≤ps;Further, the prime number satisfies 3≤p 1 ≤p 2 ≤... ≤ps ;
进一步地,所述素数,所有素数的乘积为:p=p1×p2×…×ps;Further, the prime number, the product of all prime numbers is: p=p 1 ×p 2 ×...×p s ;
进一步地,所述λ为正整数,且满足2≤λ≤p1;所述ρ为正整数,满足λ≤ρ≤p;Further, the λ is a positive integer and satisfies 2≤λ≤p 1 ; the ρ is a positive integer and satisfies λ≤ρ≤p;
进一步地,所述非负整数r0,r1,…,rλ-1,满足0≤r0<r1<…<rλ-1<p1;Further, the non-negative integers r 0 , r 1 ,...,r λ-1 satisfy 0≤r 0 <r 1 <...<r λ-1 <p 1 ;
进一步地,所述非负整数c0,c1,…,cρ-1,满足0≤c0<c1<…<cρ-1<p;Further, the non-negative integers c 0 , c 1 ,...,c ρ-1 satisfy 0≤c 0 <c 1 <...<c ρ-1 <p;
进一步地,所述二元矩阵M,M是维度为λ×ρ的任意二元矩阵;Further, the binary matrix M, M is any binary matrix with a dimension of λ×ρ;
进一步地,所述f(i,j),f(i,j)取值为f(i,j)=ri×cj。Further, the f(i,j), f(i,j) is f(i,j)=r i ×c j .
本发明与现有技术相比,具有如下优点和有益效果:Compared with the prior art, the present invention has the following advantages and beneficial effects:
本发明提出的一种基于素数乘积的准循环结构多元LDPC码构造方法,具有构造过程简单、参数灵活等优点,所得的多元LDPC码的环长较长;与基于代数结构的构造方法相比,本发明构造的多元LDPC码具有更低的硬件实现复杂度。A kind of quasi-cyclic structure multivariate LDPC code construction method based on the product of prime numbers proposed by the present invention has the advantages of simple construction process and flexible parameters, and the ring length of the obtained multivariate LDPC code is longer; compared with the construction method based on algebraic structure, The multivariate LDPC code constructed by the present invention has lower hardware implementation complexity.
附图说明Description of drawings
图1为本发明所述的一种基于素数乘积的准循环结构多元LDPC码构造方法的方法流程图;Fig. 1 is a method flowchart of a kind of quasi-cyclic structure multivariate LDPC code construction method based on prime number product of the present invention;
图2为本发明所述实施例的基于素数乘积的8-元多元LDPC码在BPSK-AWGN信道上的BER性能曲线图。FIG. 2 is a graph showing the BER performance of the 8-element multivariate LDPC code based on the product of prime numbers in the embodiment of the present invention on the BPSK-AWGN channel.
具体实施方式Detailed ways
下面结合实施例及附图对本发明作进一步详细的描述,但本发明的实施方式不限于此。The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.
实施例:Example:
一种基于素数乘积的准循环结构多元LDPC码构造方法,如图1所述,包括以下步骤:A kind of quasi-cyclic structure multivariate LDPC code construction method based on prime number product, as shown in Figure 1, comprises the following steps:
设置有限域为F8。选定s=2,p1=5,p2=7,则p=5×7=35。设置λ=4,ρ=35。对于i=0,1,2,3,设置ri=i。对于i=0,1,…,34,设置ci=i。设置矩阵M为4×35的全1矩阵。Set the finite field to F 8 . Select s=2, p 1 =5, p 2 =7, then p=5×7=35. Set λ=4, ρ=35. For i=0,1,2,3, set r i =i. For i=0,1,...,34, set c i =i. Set matrix M to be a 4×35 matrix of all 1s.
步骤一:对于i=0,1,2,3和j=0,1,…,34,生成长度为35的行向量ei,j,0,行向量ei,j,0的第i×j个分量的取值为1,其他分量的取值为“0”;对于k=1,2,…,34,行向量ei,j,k的第0个分量为行向量ei,j,k-1的第34个分量,而行向量ei,j,k的第s个分量为行向量ei,j,k-1的第s-1个分量,其中s=1,2,…,63;Step 1: For i=0,1,2,3 and j=0,1,...,34, generate a row vector e i,j,0 with a length of 35, the i-th × of the row vector e i,j,0 The value of the j component is 1, and the value of other components is "0"; for k=1,2,...,34, the 0th component of the row vector e i,j,k is the row vector e i,j , the 34th component of k-1 , and the s-th component of row vector e i,j,k is the s-1th component of row vector e i,j,k-1 , where s=1,2, ...,63;
步骤二:对于i=0,1,2,3和j=0,1,…,34,构造维度为35×35的循环置换矩阵:Step 2: For i=0,1,2,3 and j=0,1,...,34, construct a cyclic permutation matrix with a dimension of 35×35:
其中,in,
构造维度为35×1225的矩阵 和/> Construct a matrix with dimensions 35×1225 and />
步骤三:基于Λ1,Λ2,Λ3,Λ4,构造维度为140×1225的矩阵:Step 3: Based on Λ 1 , Λ 2 , Λ 3 , Λ 4 , construct a matrix with a dimension of 140×1225:
其中,in,
步骤四:对于矩阵Λ中每一个非零元“1”,随机产生一个有限域F8中的非零有限域元素并用这个有限域元素替换当前的“1”。经过上述替换过程,可得到多元LDPC码C8[1225,1085]的校验矩阵H。Step 4: For each non-zero element "1" in the matrix Λ, randomly generate a non-zero finite field element in the finite field F 8 and replace the current "1" with this finite field element. After the above replacement process, the parity check matrix H of the multivariate LDPC code C 8 [1225,1085] can be obtained.
以下仿真环境均为AWGN信道,调制均为BPSK调制,选用的译码算法有Q元和积算法和加权比特可靠度算法,所有仿真的最大迭代次数均为50。The following simulation environments are all AWGN channels, and the modulation is BPSK modulation. The selected decoding algorithms include Q-element sum-product algorithm and weighted bit reliability algorithm. The maximum number of iterations for all simulations is 50.
仿真结果见图2;其中QSPA表示Q元和积算法,wBRB算法表示加权比特可靠度算法,C8,peg[1225,1085]表示基于渐进边增长算法(PEG算法)构造的码长为1225、信息长度为1085的8元LDPC码。从图2可见,基于素数乘积构造的多元LDPC码具有良好的纠错性能。在误比特率为10-5时,基于素数乘积构造的多元LDPC码和渐进边增长算法(PEG算法)构造的等长等码率的多元LDPC码C8,peg[1225,1085]的性能相当。The simulation results are shown in Figure 2; where QSPA represents the Q element sum product algorithm, wBRB algorithm represents the weighted bit reliability algorithm, C 8, peg [1225,1085] represents the code length based on the progressive edge growth algorithm (PEG algorithm) is 1225, An 8-element LDPC code with a message length of 1085. It can be seen from Figure 2 that the multivariate LDPC code constructed based on the product of prime numbers has good error correction performance. When the bit error rate is 10 -5 , the performance of the multivariate LDPC code constructed based on the product of prime numbers and the equal-length and equal code rate multivariate LDPC code C 8,peg [1225,1085] constructed by the progressive edge growth algorithm (PEG algorithm) is comparable .
上述实施例为本发明较佳的实施方式,但本发明的实施方式并不受上述实施例的限制,其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化,均应为等效的置换方式,都包含在本发明的保护范围之内。The above-mentioned embodiment is a preferred embodiment of the present invention, but the embodiment of the present invention is not limited by the above-mentioned embodiment, and any other changes, modifications, substitutions, combinations, Simplifications should be equivalent replacement methods, and all are included in the protection scope of the present invention.
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