A CLASS OF LDPC CODE''''S CONSTRUCTION BASED ON AN ITERATIVE RANDOM METHOD

This letter gives a random construction for Low Density Parity Check (LDPC) codes, which uses an iterative algorithm to avoid short cycles in the Tanner graph. The construction method has great flexible choice in LDPC code's parameters including codelength, code rate, the least girth of the graph, the weight of column and row in the parity check matrix. The method can be applied to the irregular LDPC codes and strict regular LDPC codes. Systemic codes have many applications in digital communication, so this letter proposes a construction of the generator matrix of systemic LDPC codes from the parity check matrix. Simulations show that the method performs well with iterative decoding.     

基于二分图的乘积码迭代译码算法

该文给出了由汉明分量乘积码构造广义低密度(GLD)码的一般方法。基于所得稀疏矩阵的二分图,并结合分组码与低密度校验(LDPC)码的译码算法,设计出一种新颖的可用于乘积码迭代译码的Chase-MP算法。由于所得二分图中不含有长度为4和6的小环,因而大大减少图上迭代时外信息之间的相关性,进而提高译码性能。对加性高斯白噪声(AWGN)及瑞利(Rayleigh)衰落信道下,汉明分量 (63,57,3)2 乘积码的模拟仿真显示,该算法能够获得很好的译码性能。与传统的串行迭代Chase-2算法相比,Chase-MP算法适合用于全并行译码处理,便于硬件实现,而且译码性能优于串行迭代Chase-2算法。     

A CLASS OF LDPC CODE’S CONSTRUCTION BASED ON AN ITERATIVE RANDOM METHOD

This letter gives a random construction for Low Density Parity Check （LDPC） codes, which uses an iterative algorithm to avoid short cycles in the Tanner graph. The construction method has great flexible choice in LDPC code＇s parameters including codelength, code rate, the least girth of the graph, the weight of column and row in the parity check matrix. The method can be applied to the irregular LDPC codes and strict regular LDPC codes. Systemic codes have many applications in digital communication, so this letter proposes a construction of the generator matrix of systemic LDPC codes from the parity check matrix. Simulations show that the method performs well with iterative decoding.     

Low-density parity check codes and iterative decoding for long-haul optical communication systems

A forward-error correction (FEC) scheme based on low-density parity check (LDPC) codes and iterative decoding using belief propagation in code graphs is presented in this paper. We show that LDPC codes provide a significant system performance improvement with respect to the state-of-the-art FEC schemes employed in optical communications systems. We present a class of structured codes based on mutually orthogonal Latin rectangles. Such codes have high rates and can lend themselves to very low-complexity encoder/decoder implementations. The system performance is further improved by a code design that eliminates short cycles in a graph employed in iterative decoding.     

基于置信传播的优化译码算法研究

该文在对LDPC码的译码算法分析的基础上,针对校验矩阵中含有的环对译码算法的影响,提出了一种在置信传播算法基础之上的译码算法。该算法通过及时切断消息在环上的重传回路,可消除因校验矩阵中的环回传原始信息对译码造成的影响,保证优质的原始信息能尽可能地传播到其能传播的节点,从而提升了LDPC码的译码性能。仿真实验表明,在低信噪比的信道中,该算法具有相当于传统算法的性能和更低的计算复杂度;在良好的信道条件下可以取得比传统算法更优异的性能。     

Efficient algorithm for calculating short cycles in Tanner graph based on matrix computation

Loop distribution of Tanner graph affects the BER performance of low-density parity-check codes(LDPC) decoding.To count short cycles in the Tanner graph efficiently,a side by side recursion algorithm based on matrix computation was proposed.Firstly,5 basic graph structures were defined to realize recursive calculate in the implementation process.Compared with previous works,the algorithm provided many methods for counting the same length of cycles.The same result confirmed the correctness of the algorithm.The new algorithm could not only calculate the total number of cycles,but also gave the number each edge participating in fixed-length cycles.Its complexity was proportional to the product of D and square of N,where D was the average degree of variable nodes,and N denoted the code length.For LDPC codes,D was far less than N.For most of the LDPC codes,the calculation for numbers of cycle-length g、g+2、g+4 was only several seconds.     

Graph-based iterative decoding algorithms for parity-concatenatedtrellis codes

We construct parity-concatenated trellis codes in which a trellis code is used as the inner code and a simple parity-check code is used as the outer code. From the Tanner-Wiberg-Loeliger (1981, 1996) graph representation, several iterative decoding algorithms can be derived. However, since the graph of the parity-concatenated code contains many short cycles, the conventional min-sum and sum-product algorithms cannot achieve near-optimal decoding. After some simple modifications, we obtain near-optimal iterative decoders. The modifications include either (a) introducing a normalization operation in the min-sum and sum-product algorithms or (b) cutting the short cycles which arise in the iterative Viterbi algorithm (IVA). After modification, all three algorithms can achieve near-optimal performance, but the IVA has the least average complexity. We also show that asymptotically maximum-likelihood (ML) decoding and a posteriori probability (APP) decoding can be achieved using iterative decoders with only two iterations. Unfortunately, this asymptotic behavior is only exhibited when the bit-energy-to-noise ratio is above the cutoff rate. Simulation results show that with trellis shaping, iterative decoding can perform within 1.2 dB of the Shannon limit at a bit error rate (BER) of 4×10^-5 for a block size of 20000 symbols. For a block size of 200 symbols, iterative decoding can perform within 2.1 dB of the Shannon limit     

一种高码率低复杂度准循环LDPC码设计研究

该文设计了一种特殊的高码率准循环低密度校验(QC-LDPC)码,其校验矩阵以单位矩阵的循环移位阵为基本单元,与随机构造的LDPC码相比可节省大量存储单元。利用该码校验矩阵的近似下三角特性,一种高效的递推编码方法被提出,它使得该码编码复杂度与码长成线性关系。另外,该文提出一种分析QC-LDPC码二分图中短长度环分布情况的方法,并且给出了相应的不含长为4环QC-LDPC码的构造方法。计算机仿真结果表明,新码不但编码简单,而且具有高纠错能力、低误码平层。     

Selective avoidance of cycles in irregular LDPC code construction

This letter explains the effect of graph connectivity on error-floor performance of low-density parity-check (LDPC) codes under message-passing decoding. A new metric, called extrinsic message degree (EMD), measures cycle connectivity in bipartite graphs of LDPC codes. Using an easily computed estimate of EMD, we propose a Viterbi-like algorithm that selectively avoids small cycle clusters that are isolated from the rest of the graph. This algorithm is different from conventional girth conditioning by emphasizing the connectivity as well as the length of cycles. The algorithm yields codes with error floors that are orders of magnitude below those of random codes with very small degradation in capacity-approaching capability.     

LDPC码的改进译码算法

由于短帧长LDPC码存在很多环路,其译码性能不具有最优性.本文首先推导了有环路LDPC码的概率译码算法,然后在传统的概率译码算法引入了修正系数,从而减小了环路对译码性能的影响.仿真结果表明,采用改进的译码算法可以提高译码性能.     

A high‐performance belief propagation decoding algorithm for codes with short cycles

The simplicity of decoding is one of the most important characteristics of the low density parity check (LDPC) codes. Belief propagation (BP) decoding algorithm is a well‐known decoding algorithm for LDPC codes. Most LDPC codes with long lengths have short cycles in their Tanner graphs, which reduce the performance of the BP algorithm. In this paper, we present 2 methods to improve the BP decoding algorithm for LDPC codes. In these methods, the calculation of the variable nodes is controlled by using “multiplicative correction factor” and “additive correction factor.” These factors are obtained for 2 separate channels, namely additive white Gaussian noise (AWGN) and binary symmetric channel (BSC), as 2 functions of code and channel parameters. Moreover, we use the BP‐based method in the calculation of the check nodes, which reduces the required resources. Simulation results show the proposed algorithm has better performance and lower decoding error as compared to BP and similar methods like normalized‐BP and offset‐BP algorithms.     

Regular Low-Density Parity-Check codes based on shifted identity matrices

This paper extends the class of Low-Density Parity-Check （LDPC） codes that can be constructed from shifted identity matrices. To construct regular LDPC codes, a new method is proposed. Two simple inequations are adopted to avoid the short cycles in Tanner graph, which makes the girth of Tanner graphs at least 8. Because their parity-check matrices are made up of circulant matrices, the new codes are quasi-cyclic codes. They perform well with iterative decoding.     

低密度奇偶校验码码字构造的消环算法

低密度奇偶校验码(LDPC)的性能取决于多种因素,包括度分布对、码字的长度以及环的分布。环的存在会影响LDPC码的译码门限和误码平层,尤其是长度比较小的环对LDPC码的性能影响很大。因此,有必要在构造LDPC码时消去长度比较小的环。文中提供了一种有效的消环算法,降低了LDPC码的误码平层。     

Design of Quasi‐Cyclic Low‐Density Parity Check Codes with Large Girth

In this paper we propose a graph‐theoretic method based on linear congruence for constructing low‐density parity check (LDPC) codes. In this method, we design a connection graph with three kinds of special paths to ensure that the Tanner graph of the parity check matrix mapped from the connection graph is without short cycles. The new construction method results in a class of (3, ρ)‐regular quasi‐cyclic LDPC codes with a girth of 12. Based on the structure of the parity check matrix, the lower bound on the minimum distance of the codes is found. The simulation studies of several proposed LDPC codes demonstrate powerful bit‐error‐rate performance with iterative decoding in additive white Gaussian noise channels.     

累加交叉并行级联单奇偶校验码的低复杂度译码算法

累加交叉并行级联单奇偶校验(A-CPSPC)码是一种新的纠错编码,其编码结构简单并具有较好的误比特率性能。该文针对A-CPSPC码的局部编码结构提出了一种低复杂度的最大后验(MAP)局部译码算法,该方法利用基于双向消息传递原则的和积算法(SPA)进行局部译码,消除了短环对局部译码性能的影响。分析及仿真表明,传统的置信传播算法并不适用于A-CPSPC码,该文提出的局部译码算法与基于BCJR算法的局部译码算法的性能一致,且复杂度更低。     

一种基于奇偶校验码级联极化码的低复杂度译码算法

极化码作为一种纠错码,具有较好的编译码性能,已成为 5G 短码控制信道的标准编码方案。但在码长较短时,其性能不够优异。作为一种新型级联极化码,奇偶校验码与极化码的级联方案提高了有限码长的性能,但是其译码算法有着较高的复杂度。该文针对这一问题,提出一种基于奇偶校验码级联极化码的串行抵消局部列表译码(PC-PSCL)算法,该算法在编码前进行外码构造,通过高斯近似(GA)得到的子信道错误概率选取较不可靠的信息位,对选取的较不可靠的信息位进行串行抵消列表(SCL)译码和奇偶校验,其余信息比特仅进行串行抵消(SC)译码。仿真结果表明,在高斯信道下,当码长为512,码率为1/2,误帧率为10^–3,最大列表长度为8时,该文提出的低复杂度译码算法比SCL译码算法获得了0.5 dB的增益;与基于奇偶校验的SCL译码算法性能相近,但是空间复杂度和时间复杂度分别降低了38.09%, 15.63%。     

Error rate estimation of low-density parity-check codes on binary symmetric channels using cycle enumeration

The performance of low-density parity-check (LDPC) codes decoded by hard-decision iterative decoding algorithms can be accurately estimated if the weight J and the number |E_J| of the smallest error patterns that cannot be corrected by the decoder are known. To obtain J and |E_J|, one would need to perform the direct enumeration of error patterns with weight ι ⩽ J. The complexity of enumeration increases exponentially with J, essentially as η^J, where η is the code block length. This limits the application of direct enumeration to codes with small η and J. In this letter, we approximate J and |E_J | by enumerating and testing the error patterns that are subsets of short cycles in the code's Tanner graph. This reduces the computational complexity by several orders of magnitude compared to direct enumeration, making it possible to estimate the error rates for almost any practical LDPC code. To obtain the error rate estimates, we propose an algorithm that progressively improves the estimates as larger cycles are enumerated. Through a number of examples, we demonstrate that the proposed method can accurately estimate both the bit error rate (BER) and the frame error rate (FER) of regular and irregular LDPC codes decoded by a variety of hard-decision iterative decoding algorithms.     

Memory-efficient sum-product decoding of LDPC codes

Low-density parity-check (LDPC) codes perform very close to capacity for long lengths on several channels. However, the amount of memory (fixed-point numbers that need to be stored) required for implementing the message-passing algorithm increases linearly as the number of edges in the graph increases. In this letter, we propose a decoding algorithm for decoding LDPC codes that reduces the memory requirement at the decoder. The proposed decoding algorithm can be analyzed using density evolution; further, we show how to design good LDPC codes using this. Results show that this algorithm provides almost the same performance as the conventional sum-product decoding of LDPC codes.     

LDPC码在因子图上的构造及其译码

LDPC码是一种可以接近香农限的线性分组码,可通过稀疏奇偶校验矩阵来构造。也可以用因子图来构成。根据LDPC码的不同构成方法至今已提出了数种不同的译码方法。本文介绍了基于因子图的LDPC码的构造方法,分析了和一积(SPA)译码算法的基本原理,最后详细讨论了用SPA算法对LDPC码进行译码的过程。     

Efficient priority-first search maximum-likelihood soft-decisiondecoding of linear block codes

The authors present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here converts the decoding problem into a search problem through a graph that is a trellis for an equivalent code of the transmitted code. A generalized Dijkstra's algorithm, which uses a priority-first search strategy, is employed to search through this graph. This search is guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of the transmitted code. This function f is used to reduce drastically the search space and to make the decoding efforts of this decoding algorithm adaptable to the noise level. For example, for most real channels of the 35 000 samples tried, simulation results for the (128,64) binary extended BCH code show that the proposed decoding algorithm is fifteen orders of magnitude more efficient in time and in space than that proposed by Wolf (1978). Simulation results for the (104, 52) binary extended quadratic residue code are also given