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.     

Efficient maximum likelihood decoding of linear block codes using a trellis

It is shown that soft decision maximum likelihood decoding of any(n,k)linear block code overGF(q)can be accomplished using the Viterbi algorithm applied to a trellis with no more thanq^{(n-k)}states. For cyclic codes, the trellis is periodic. When this technique is applied to the decoding of product codes, the number of states in the trellis can be much fewer thanq^{n-k}. For a binary(n,n - 1)single parity check code, the Viterbi algorithm is equivalent to the Wagner decoding algorithm.     

Iterative reliability-based decoding of low-density parity checkcodes

In this paper, reliability based decoding is combined with belief propagation (BP) decoding for low-density parity check (LDPC) codes. At each iteration, the soft output values delivered by the BP algorithm are used as reliability values to perform reduced complexity soft decision decoding of the code considered. This approach allows to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered. Trade-offs between decoding complexity and error performance are also investigated. In particular, a stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach. Simulation results for several Gallager (1963, 1968) LDPC codes and different set cyclic codes of hundreds of information bits are given and elaborated     

Iterative decoding of one-step majority logic deductible codesbased on belief propagation

Previously, the belief propagation (BP) algorithm has received a lot of attention in the coding community, mostly due to its near-optimum decoding for low-density parity check (LDPC) codes and its connection to turbo decoding. In this paper, we investigate the performance achieved by the BP algorithm for decoding one-step majority logic decodable (OSMLD) codes. The BP algorithm is expressed in terms of likelihood ratios rather than probabilities, as conventionally presented. The proposed algorithm fits better the decoding of OSMLD codes with respect to its numerical stability due to the fact that the weights of their check sums are often much higher than that of the corresponding LDPC codes. Although it has been believed that OSMLD codes are far inferior to LDPC codes, we show that for medium code lengths (say between 200-1000 bits), the BP decoding of OSMLD codes can significantly outperform BP decoding of their equivalent LDPC codes. The reasons for this behavior are elaborated     

LT码的增强型BP译码算法

传统的LT码采用的BP译码算法,当不存在度1编码分组时会导致BP译码算法失败,不能继续译码.为了提高译码的成功率,分析了剩余编码分组的结构,提出LT码的再次译码算法(Again Belief Propagation decoding algorithm,ABP).算法主要思想是BP译码失败后,查找满足条件的可译结构,继续译码,直到译码成功或再次失败,如果失败重复上面步骤直到译码成功或可译结构不存在,从理论上分析了可译结构存在的概率.仿真结果显示译码成功率得到提高.     

系统RA码的基于WBF策略的改进BP译码算法

 针对重复累积(RA)码译码算法(BP算法和最小和算法)复杂度高或纠错性能下降的问题,将加权位翻转WBF的思想用于改进BP算法,提出了基于WBF策略的改进BP译码算法. 在每次迭代译码中若未能译出合法码字,则按一定规则进行位翻转操作,以期获得合法码字. 仿真结果表明,本算法能有效降低系统RA码的运算复杂度,且能保持优异的译码性能.     

基于相对残余度的LDPC码置信传播译码调度算法(英文)

Two Relative-Residual-based Dynamic Schedules(RRDS) for Belief Propagation(BP) decoding of Low-Density Parity-Check(LDPC) codes are proposed,in which the Variable code-RRDS(VN-RRDS) is a greediness-reduced version of the Check code-RRDS(CN-RRDS).The RRDS only processes the variable(or check) node,which has the maximum relative residual among all the variable(or check) nodes in each decoding iteration,thus keeping less greediness and decreased complexity in comparison with the edge-based Variable-to-Check Re...     

Application of Beam Search for the decoding of one class of LDPC codes

For one class of Low-Density Parity-Check（LDPC）codes with low row weight in their parity check matrix,a new Syndrome Decoding（SD）based on the heuristic Beam Search（BS）,labeled as SD-BS,is put forward to improve the error performance.First,two observations are made and verified by simulation results.One is that in the SNR region of interest,the hard-decision on the corrupted sequence yields only a handful of erroneous bits.The other is that the true error pattern for the nonzero syndrome has a high probability to survive the competition in the BS,provided sufficient beam width.Bearing these two points in mind,the decoding of LDPC codes is transformed into seeking an error pattern with the known decoding syndrome.Secondly,the effectiveness of SD-BS depends closely on how to evaluate the bit reliability.Enlightened by a bit-flipping definition in the existing literature,a new metric is employed in the proposed SD-BS.The strength of SD-BS is demonstrated via applying it on the corrupted sequences directly and the decoding failures of the Belief Propagation（BP）,respectively.     

Turbo decoding of product codes using adaptive belief propagation

The adaptive belief propagation (ABP) algorithm was recently proposed by Jiang and Narayanan for the soft decoding of Reed-Solomon (RS) codes. In this paper, simplified versions of this algorithm are investigated for the turbo decoding of product codes. The complexity of the turbo-oriented adaptive belief propagation (TAB) algorithm is significantly reduced by moving the matrix adaptation step outside of the belief propagation iteration loop. A reduced-complexity version of the TAB algorithm that offers a trade-off between performance and complexity is also proposed. Simulation results for the turbo decoding of product codes show that belief propagation based on adaptive parity check matrices is a practical alternative to the currently very popular Chase-Pyndiah algorithm.     

Near optimum universal belief propagation based decoding oflow-density parity check codes

In this paper, we propose a belief-propagation (BP)-based decoding algorithm which utilizes normalization to improve the accuracy of the soft values delivered by a previously proposed simplified BP-based algorithm. The normalization factors can be obtained not only by simulation, but also, importantly, theoretically. This new BP-based algorithm is much simpler to implement than BP decoding as it requires only additions of the normalized received values and is universal, i.e., the decoding is independent of the channel characteristics. Some simulation results are given, which show this new decoding approach can achieve an error performance very close to that of BP on the additive white Gaussian noise channel, especially for low-density parity check (LDPC) codes whose check sums have large weights. The principle of normalization can also be used to improve the performance of the max-log-MAP algorithm in turbo decoding, and some coding gain can be achieved if the code length is long enough     

任意列重大围长QC-LDPC码的确定性构造

针对准循环低密度奇偶校验（Quasi-Cyclic Low-Density Parity-Check,QC-LDPC）码中准循环基矩阵的移位系数确定问题,提出基于等差数列的确定方法.该方法构造的校验矩阵围长为8,列重可任意选取,移位系数由简单的数学表达式确定,编码复杂度与码长呈线性关系,节省了编解码存储空间.研究结果表明,列重和围长是影响码字性能的重要因素.在加性高斯白噪声（Additive White Gauss Noise,AWGN）信道和置信传播（Belief Propagation,BP）译码算法下,该方法构造的码字在短码时可以获得与IEEE 802.11n、802.16e码相一致的性能,在长码时误比特率性能接近DVB-S2码.同时表明该方法对码长和码率参数的设计具有较好的灵活性.     

高性能时不变LDPC卷积码构造算法研究

该文基于由QC-LDPC码获得时不变LDPC卷积码的环同构方法,设计了用有限域上元素直接获得时不变LDPC卷积码多项式矩阵的新算法。以MDS卷积码为例,给出了一个具体的构造过程。所提构造算法可确保所获得的时不变LDPC卷积码具有快速编码特性、最大可达编码记忆以及设计码率。基于滑动窗口的BP译码算法在AWGN信道上的仿真结果表明,该码具有较低的误码平台和较好的纠错性能。     

基于PD-CNN的Polar码译码算法

针对传统Polar码译码算法在相关噪声信道下性能严重下降的问题,提出了一种基于前置预判-卷积神经网络（Prior Decision-Convolutional Neural Networks,PD-CNN）的译码算法。通过前置预判深度优化CNN,使其准确地估计信道噪声并使残余噪声尽可能遵循高斯分布,再根据残余噪声分布统计更新出可靠的似然比信息。分析了不同译码算法对不同码率Polar码在不同噪声相关强度下的译码性能,并与本文所提出的译码算法进行对比。仿真结果表明:在相关噪声信道下,当误码率为10-5时,本文所提出的译码算法与标准置信度传播算法相比可获得约2.5 Bd的增益。此外,在高信噪比时,与置信度传播-卷积神经网络算法相比,本文提出的译码算法具有相同的性能,但复杂度更低,译码延迟最大可减少42%。      

LDPC码BP译码算法研究

本文研究了LDPC码的译码。深入研究了概率域BP算法和LLRBP算法。通过计算机仿真,比较了不同码长和不同迭代次数对译码性能的影响。通过计算机仿真得到在LDPC译码过程中,LDPC码的码字越长,构造的校验矩阵中短周期就越短,性能提高就越为明显。同时得到在LDPC译码过程中,迭代次数越多,各节点获得的信息的准确性就越高,性能提高就越为明显。     

一种改进的RA译码算法

重复累积(RA)码译码使用置信传播(BP)算法,具有接近香农限的性能,但校验节点更新时使用复杂的双曲正切函数和反双曲正切函数,算法复杂度较高。为了降低译码算法的复杂度,且具有较好的性能,该文将查表法和分段函数近似法结合起来,提出了一种改进的译码算法。该算法采用分段的一次函数,去近似BP算法检验节点变换化简后的原函数,采用非常小的查找表得到一个校正值,用校正值去修正近似函数和变换化简后的原函数之间的误差,很好地避免了复杂函数的计算,且误差极小。该算法大大降低了译码算法的复杂度,且具有接近BP算法的译码性能。     

新型LT码编译码方法及其在认知无线电中的应用

Luby变换(LT)码作为一种抗干扰编码技术,应用于认知无线电系统,可提高次用户数据传输的可靠性。编译码是影响LT码抗干扰性能的关键因素。为提高数据传输的可靠性和速度,该文提出一种适用于认知无线电系统的LT码联合泊松鲁棒孤子分布-叠层(CPRSD-H)编译码算法。编码过程中,编码器首先采用CPRSD进行编码产生编码分组和编码矩阵,随后通过编码矩阵中度数为1和度数为2对应的列向量携带双层信息:度数为1和度数为2的编码分组和与其相连接的输入分组的连接关系;部分原始数据信息。译码过程中,译码器首先通过第1层存储信息采用置信传播(BP)算法译码完成,随后一些未被成功译出的信息再通过第2层存储信息进行填补。仿真结果表明,将CPRSD-H编译码算法应用于认知无线电系统中,能够显著降低LT码的误比特率(BER),提高次用户有效吞吐量以及加快LT码编译码速度。     

Computationally efficient decoding of LDPC codes

A computationally efficient algorithm for the decoding of low-density parity check codes is introduced. Instead of updating all bit and check nodes at each decoding iteration, the developed algorithm only updates unreliable check and bit nodes. A simple reliability criteria is developed to determine the active bit and check nodes per decoding iteration. Based on the developed technique, significant computation reductions are achieved with very little or no loss in the BER performance of the LDPC codes. The proposed method can be implemented with a slight modification to the sum-product algorithm with negligible additional hardware complexity.     

Performance of a general decoding technique over the class ofrandomly chosen parity check codes

The paper extends a general decoding technique developed by Metzner and Kapturowski (1990) for concatenated code outer codes and for file disagreement location. That work showed the ability to correct most cases of d-2 or fewer erroneous block symbols, where d is the outer code minimum distance. Any parity check code can be used as the basis for the outer codes, and yet decoding complexity increases at most as the third power of the code length. In this correspondence, it is shown that, with a slight modification and no significant increase in complexity, the general decoding technique can be applied to the correction of many other cases beyond the code minimum distance. By considering average performance over all binary randomly chosen codes, it is seen that most error patterns of t_M or fewer block errors can be corrected, where: 1) t_M in most cases is much greater than the code minimum distance, and 2) asymptotically, the ratio of t_M to the theoretical maximum (the number of parity symbol blocks) approaches 1. Moreover, most cases of noncorrectable error block patterns are detected     

Linear programming decoding: The ultimate decoding technique for low density parity check codes

Linear programming (LP) decoding is an alternative to iterative algorithms for decoding low density parity check (LDPC) codes. Although the practical performance of LP decoding is comparable to message-passing decoding, a significant advantage is its relative amenability to nonasymptotic analysis. Moreover, there turn out to be a number of important theoretical connections between the LP decoding and standard forms of iterative decoding. These connections allow theoretical insight from the LP decoding perspective to be transferred to iterative decoding algorithms. These advantages encouraged many researchers to work in this recent decoding technique for LDPC codes. In this paper, LP decoding for LDPC code is extensively reviewed and is discussed in different segmented areas.