光传输系统中一种新颖的SCG-LDPC码译码算法分析

依据SCG-LDPC码的结构特点提出了一种高效的分层可靠置信传播(HRBP)译码算法,该算法结合分层迭代与可靠度判决测量有效降低后续迭代过程中的变量节点数,同时加快了收敛速度。针对适用于光传输系统的SCG-LDPC(3 969,3 720)码进行仿真,仿真结果表明HRBP算法与传统的BP算法相比,在保证性能的同时大大降低了运算量,在阈值为15时,HRBP译码算法误码率性能与BP译码算法相当,但是后续迭代的变量节点数在高信噪比下相比BP译码算法减少约69%,当阈值进一步增大时,HRBP算法将逐步退化为分层置信传播(Layered-BP)译码算法。     

基于振荡迭代的修正BP译码算法

针对中高信噪比(SNR)下低密度奇偶校验(LDPC)译码错误振荡迭代不收敛,提出了基于置信传播(BP)算法的修正LDPC译码算法,即软值归零BP算法。该算法通过将振荡迭代的变量节点传递的外信息置零,减少错误信道消息对迭代译码的影响,较大地改善了译码性能。而且,还给出了振荡迭代节点的判定准则,提高了振荡迭代节点判定的准确性。仿真结果表明,在中高信噪比区且译码迭代次数相同的情况下,该算法能比BP算法获得更好的译码性能。     

Improving belief propagation on graphs with cycles

In this letter, we propose two modifications to belief propagation (BP) decoding algorithm. The modifications are based on reducing the reliability of messages throughout the iteration process, and are particularly effective for short low-density parity-check codes, where the existence of cycles makes the original BP algorithm perform suboptimal. The proposed algorithms, referred to as "normalized BP" and "offset BP," reduce the absolute value of the outgoing log-likelihood ratio messages at variable nodes by using a multiplicative factor and an additive factor, respectively. Simulation results show that both algorithms perform more or less the same, and both outperform BP in error performance.     

Sequential message-passing decoding of LDPC codes by partitioning check nodes

In this paper, we analyze the sequential message- passing decoding algorithm of low-density parity-check (LDPC) codes by partitioning check nodes. This decoding algorithm shows better bit error rate (BER) performance than the conventional message-passing decoding algorithm, especially for the small number of iterations. Analytical results indicate that as the number of partitioned subsets of check nodes increases, the BER performance is improved. We also derive the recursive equations for mean values of messages at check and variable nodes by using density evolution with a Gaussian approximation. From these equations, the mean values are obtained at each iteration of the sequential decoding algorithm and the corresponding BER values are calculated. They show that the sequential decoding algorithm converges faster than the conventional one. Finally, the analytical results are confirmed by the simulation results.     

一种改进的无线光通信LDPC码译码算法

针对无线光通信中低密度奇偶校验码(LDPC)置信传播(BP)译码算法复杂度高及置信度振荡造成译码错误等缺点,基于对数BP算法提出了一种改进的译码算法。改进的译码算法在校验节点运算时,判断输入到校验节点消息的最小值与某个门限的大小,根据比较结果,分别用消息最小值或若干个最小值进行运算,在损失很少性能的情况下降低了运算复杂度;同时在比特节点采用振荡抵消处理运算,提高了算法的性能增益。最后在对数正态分布湍流信道模型下,分别对比特充分交织和交织深度为16的情况进行了仿真实验。仿真结果表明,改进的译码算法与BP算法相比,大幅度降低了计算复杂度,而且译码性能有一定的优势,收敛速度损失很少;而相对于最小和算法,改进的算法虽然译码复杂度有所增加,但误码率性能有明显的优势,并且收敛速度也优于最小和算法。因此,改进的译码算法是无线光通信中LDPC码译码算法复杂度和性能之间一个较好的折中处理方案。     

一种低迭代次数的极化码置信传播译码算法

针对置信传播(Belief Propagation,BP)译码算法在迭代次数较多时吞吐量和译码时延性能提升受限的问题,提出了一种低迭代次数的极化码BP译码算法,通过采用比特翻转和子信道冻结的方式,降低译码过程中的迭代次数.仿真结果表明,相对于传统极化码BP译码算法(设置最大迭代次数为40次),所提算法在信噪比为3 dB...     

光通信系统中一种改进的LLR-BP译码算法

光通信系统中低密度奇偶校验(Low-density Parity-check,LDPC)码采用对数似然比置信传播(Log-likelihood Ratio Belief Propagation,LLR-BP)算法进行译码时,在高信噪比区域迭代译码过程中会出现变量节点外部信息振荡不收敛而导致译码纠错性能的降低.为满足光通信系统的要求,提出了一种削弱外部消息振荡的改进LLR-BP译码算法.该算法通过引入加权系数平衡前后两次迭代之间变量节点传递的外部信息,明显减缓了外部信息的振荡现象.仿真结果表明:与传统LLR-BP译码算法相比,该改进LLR-BP算法具有更佳的误码性能,同时降低变量节点外部信息振荡现象并加快了译码的收敛速度.     

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     

LDPC短码的编译码研究

这里研究了原模图LDPC码和BP译码算法,首先提出了一种基于PEG算法构造原模图LDPC码的算法,该码字在码率为1/2,码长256比特的情况下,译码性能超过了PEG算法,然后针对LDPC短码不可避免存在四环的特殊性,提出了一种修正四环中变量节点迭代信息的BP译码改进算法,使得具有四环的LDPC短码的译码性能得到较大提升。     

系统极化码的置信传播译码性能分析

置信传播( BP)算法可以为系统极化码提供软信息作为判决依据,也可以为系统极化码在级联迭代译码中提供交换软信息。在详细描述基于信道极化结构的置信传播算法基础上,比较了系统极化码在软信息判决方法和极化编码判决方法下错误率性能的差异。仿真结果表明,软信息判决方法可以提高系统极化码的误比特率,在高信噪比下误帧率方面也略有提高。     

基于Polar码的速率兼容调制方案设计

提出了一种基于Polar码的速率兼容调制（rate compatible modulation,RCM）联合设计方案,用于提高无线通信频谱利用率.相应地设计了基于置信度传播（belief propagation,BP）和软抵消（soft cancellation,SCAN）的接收端高效联合迭代译码算法.根据该算法可通过优化变量节点对数似然比（log-likelihood ratio,LLR）信息迭代方式以及采用限制译码符号上限的改进措施,提高译码过程的稳定性与时效性.与距离优化的级联低密度奇偶校验（low-density parity-check codes,LDPC）码RCM方案对比结果表明,提出的高效联合迭代译码算法在低信噪比（signal noise ratio,SNR）下有更低的译码复杂度,并且具有更优的吞吐量和误码率性能.因此,本文所提方案适合在恶劣信道条件下的无线传输.     

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。     

使用交互式编解码机制的分布式视频编码研究

为了克服Slepian-Wolf编码不存在统一编码以及采用的无记忆信道模型不符合实际等问题,运用交互式编解码(IED)方式,建立了统一编码,构建了有记忆的有限状态信道(FSC)模型,同时设计了一种适合FSC的用于LDPC解码的置信传播算法。实验结果表明,实现后的IED相比非IED具有更低的误码率(BER),且与理论极限码率更加逼近,实际视频序列的测试结果显示,实现的IED分布式视频编码系统较LDPC算法有2dB左右的率失真性能增益。     

A differential binary message-passing LDPC decoder

In this paper, we propose a binary message-passing algorithm for decoding low-density parity-check (LDPC) codes. The algorithm substantially improves the performance of purely hard-decision iterative algorithms with a small increase in the memory requirements and the computational complexity. We associate a reliability value to each nonzero element of the code's parity-check matrix, and differentially modify this value in each iteration based on the sum of the extrinsic binary messages from the check nodes. For the tested random and finite-geometry LDPC codes, the proposed algorithm can perform as close as about 1 dB and 0.5 dB to belief propagation (BP) at the error rates of interest, respectively. This is while, unlike BP, the algorithm does not require the estimation of channel signal to noise ratio. Low memory and computational requirements and binary message-passing make the proposed algorithm attractive for high-speed low-power applications.     

Design of Irregular LDPC Codes for BIAWGN Channels with SNR Mismatch

Belief propagation (BP) algorithm for decoding lowdensity parity-check (LDPC) codes over a binary input additive white Gaussian noise (BIAWGN) channel requires the knowledge of the signal-to-noise ratio (SNR) at the receiver to achieve its ultimate performance. An erroneous estimation or the absence of a perfect knowledge of the SNR at the decoder is referred to as ?SNR mismatch?. SNR mismatch can significantly degrade the performance of LDPC codes decoded by the BP algorithm. In this paper, using extrinsic information transfer (EXIT) charts, we design irregular LDPC codes that perform better (have a lower SNR threshold) in the presence of mismatch compared to the conventionally designed irregular LDPC codes that are optimized for zero mismatch. Considering that min-sum (MS) algorithm is the limit of BP with infinite SNR over-estimation, the EXIT functions generated in this work can also be used for the efficient analysis and design of LDPC codes under the MS algorithm.     

Hybrid Iterative Decoding for Low-Density Parity-Check Codes Based on Finite Geometries

In this letter, a two-stage hybrid iterative decoding algorithm which combines two iterative decoding algorithms is proposed to reduce the computational complexity of finite geometry low-density parity-check (FG-LDPC) codes. We introduce a fast weighted bit-flipping (WBF) decoding algorithm for the first stage decoding. If the first stage decoding fails, the decoding is continued by the powerful belief propagation (BP) algorithm. The proposed hybrid decoding algorithm greatly reduces the computational complexity while maintains the same performance compared to that of using the BP algorithm only.     

Error performances of multi shift-register convolutional self-doubly-orthogonal codes

A class of orthogonal convolutional codes using a multi shift-register encoder and featuring self-doubly-orthogonal properties is analyzed under iterative decoding. The lower bounds of error performances of these codes can be approached within typically three to five iterations at moderate signal-to-noise ratios using either iterative threshold (TH) decoding or belief propagation (BP) decoding. Compared with iterative BP decoding, it is shown that iterative threshold decoding for these codes yields a much lower complexity at the same decoding latency.     

基于DTMB标准的最小和积译码改进算法

基于最小和积(MSA)的译码算法,是对数似然比BP(LLR-BP)算法的近似,通过在译码算法中的变量处理阶段添加IIR滤波,同时结合迭代终止准则,实现了一种修改的归一化最小和积算法.该算法仿真建立在DTMB标准中的LDPC码元基础上,仿真结果表明,该算法与常规的归一化译码算法相比,在性能无损失甚至于有所改善的情况下大幅减少了迭代次数,具有很好的使用价值.     

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 Belief Propagation for Decoding LDPC Codes in the Presence of Channel Estimation Error

In this paper, we investigate the performance of the belief propagation (BP) algorithm for decoding low-density parity-check codes over the additive white Gaussian noise channel when there is an incorrect estimate of the channel signal-to-noise ratio (SNR) (referred to as "SNR mismatch") at the decoder. At the extremes for over- and underestimation of SNR, the performance of BP tends to that of min-sum algorithm and the channel bit-error rate, respectively. Our results for regular codes indicate that the sensitivity to mismatch increases by increasing the variable-node degree and by decreasing the check-node degree. The effect of variable-node degree, however, appears to be more profound, such that at a given rate, the codes with the smallest variable and check degrees are more robust against SNR mismatch. For irregular codes, by comparing the thresholds of a few ensembles, we demonstrate that the ensemble which performs better in the absence of mismatch can perform worse in the presence of it. To obtain our asymptotic results, we propose a computationally efficient method based on the Gaussian approximation of density evolution in the presence of SNR mismatch. We also show that the asymptotic results are consistent with simulation results for codes with finite block lengths