Application of the Henon Chaotic Model on to the Design of Low Density Parity Check Codes

A new method to design parity-check matrix based on Henon chaos model is presented. The designed parity-check matrix is with rather random behavior. Simulation results show that the proposed method makes an improvement in bit error rate （BER） performance by 0.4 dB compared with that of Luby for AWGN channel. The proposed method decreases the complexity of decoding significantly, and improves the error correcting performance of LDPC codes. It has been shown that Henon chaotic model is a powerful tool for construction of good LDPC codes, which make it possible to apply the LDPC code in real communication systems.

Implementation of low-density parity-check codes decoder for CCSDS standard

The complexity/performance balanced decoder for low-density parity-check （LDPC） codes is preferred in practical wireless communication systems. A low complexity LDPC decoder for the Consultative Committee for Space Data Systems （CCSDS） standard is achieved in DSP. An ap- proximate decoding algorithm, normalized rain-sum algorithm, is used in the implementation for its low amounts of computation. To reduce the performance loss caused by the approximation, the pa- rameters of the normalized min-sum algorithm are determined by calculating and finding the mini- mum value of thresholds through density evolution. The minimum value which indicates the best per- formance of the decoding algorithm is corresponding with the optimized parameters. In implementa- tion, the memory cost is saved by decomposing the parity-check matrix into submatrices to store and the computation of passing message in decoding is accelerated by using the intrinsic function of DSP. The performance of the decoder with optimized factors is simulated and compared with the ideal BP decoder. The result shows they have about the same performance.

Low-Complexity Optimization Algorithm for Irregular Low-Density Parity-Check Codes

A low-complexity algorithm is proposed in this paper in order to optimize irregular low-density parity-check （LDPC） codes.The algorithm proposed can calculate the noise threshold by means of a one-dimensional density evolution and search the optimal degree profiles with fast-convergence differential evolution,so that it has a lower complexity and a faster convergence speed.Simulation resuits show that the irregular LDPC codes optimized by the presented algorithm can also perform better than Turbo codes at moderate block length even with less computation cost.

DESIGN OF LOW-DENSITY PARITY CHECK CODES FOR MIMO SYSTEMS WITH DOUBLY-ITERATIVE RECEIVERS

In this paper, the Multiple Input Multiple Output (MIMO) doubly-iterative receiver which consists of the Probabilistic Data Association detector (PDA) and Low-Density Parity-Check Code (LDPC) decoder is developed. The receiver performs two iterative decoding loops. In the outer loop, the soft information is exchanged between the PDA detector and the LDPC decoder. In the inner loop, it is exchanged between variable node and check node decoders inside the LDPC decoder. On the light of the Extrinsic Information Transfer (EXIT) chart technique, an LDPC code degree profile optimization algorithm is developed for the doubly-iterative receiver. Simulation results show the doubly-receiver with optimized irregular LDPC code can have a better performance than the one with the regular one.

Low-Density Parity-Check Codes: Research Status and Development Direction

In this paper, we conclude five kinds of methods for construction of the regular low-density parity matrix H and three kinds of methods for the construction of irregular low-density parity-check matrix H. Through the analysis of the code rate and parameters of these eight kinds of structures, we find that the construction of low-density parity-check matrix tends to be more flexible and the parameter variability is enhanced. We propose that the current development cost should be lower with the progress of electronic technology and we need research on more practical Low-Density Parity-Check Codes (LDPC). Combined with the application of the quantum distribution key, we urgently need to explore the research direction of relevant theories and technologies of LDPC codes in other fields of quantum information in the future.

Data Gathering in Wireless Sensor Networks Via Regular Low Density Parity Check Matrix

A great challenge faced by wireless sensor networks(WSNs) is to reduce energy consumption of sensor nodes. Fortunately, the data gathering via random sensing can save energy of sensor nodes. Nevertheless, its randomness and density usually result in difficult implementations, high computation complexity and large storage spaces in practical settings. So the deterministic sparse sensing matrices are desired in some situations. However,it is difficult to guarantee the performance of deterministic sensing matrix by the acknowledged metrics. In this paper, we construct a class of deterministic sparse sensing matrices with statistical versions of restricted isometry property(St RIP) via regular low density parity check(RLDPC) matrices. The key idea of our construction is to achieve small mutual coherence of the matrices by confining the column weights of RLDPC matrices such that St RIP is satisfied. Besides, we prove that the constructed sensing matrices have the same scale of measurement numbers as the dense measurements. We also propose a data gathering method based on RLDPC matrix. Experimental results verify that the constructed sensing matrices have better reconstruction performance, compared to the Gaussian, Bernoulli, and CSLDPC matrices. And we also verify that the data gathering via RLDPC matrix can reduce energy consumption of WSNs.

基于Golomb Ruler的QC-LDPC码构造方法

针对准循环低密度奇偶校验(QC-LDPC)码中短环结构会影响其纠错性能的问题,基于Golomb Ruler提出了一种新颖的围长为8的QC-LDPC码构造方法。该方法先根据码长码率的需求,从Golomb Ruler中选择部分元素构造一个集合,结合指数矩阵中元素所在位置的四六环特性,通过搜索算法,依次找出符合无四六环条件的元素得到另一个集合,然后构造相应的指数矩阵,最后得到其奇偶校验矩阵。仿真结果表明:在误码率为10^(-6)时,所构造的GR-QC-LDPC码与同码率码长的其他4种QC-LDPC码的码型相比,其净编码增益均有一定的提高,且无明显错误平层现象。

基于可靠度差值特征的自适应判决多元LDPC译码算法

利用变量节点符号可靠度在迭代过程中的分布特征,提出了一种基于可靠度差值特征的自适应判决多元低密度奇偶校验(Low Density Parity Check, LDPC)译码算法。整个迭代过程划分为两个阶段,针对不同阶段节点可靠度的差值特征分别采用不同的判决策略:前期阶段,采用传统的基于最大可靠度的判决策略;后期阶段,根据最大、次大可靠度之间的差值特征,设计自适应的码元符号判决策略。仿真结果表明,所提算法在相当的译码复杂度前提下,能获得0.15~0.4 dB的性能增益。同时,对于列重较小的LDPC码,具有更低的译码错误平层。

基于帧交错的LDPC译码器流水结构设计

低密度奇偶校验码(LDPC)的译码器通常采用基于节点置信度更新迭代的算法,这种算法可以并行实现,具有非常高的吞吐量。在此提出了一种具有高硬件利用效率(HUE)的帧交错译码结构,并提供了一种用于层内节点重排序的动态规划方法,解决内存访问冲突问题。与现有的结构相比,该结构可以实现更高的硬件利用效率。

基于残差分层的归一化最小和LDPC译码算法

为了进一步缩小最小和(min-sum, MS)算法和置信传播(belief propagation, BP)算法译码性能的差距,提高归一化最小和(normalized min-sum, NMS)算法的译码性能,提出了一种基于残差分层的改进归一化最小和低密度奇偶校验(low density parity check,LDPC)译码算法。首先定量分析MS算法存在的高估问题,利用BP算法和MS算法检验节点LLR消息的比值特性,求其归一化因子。为了降低译码的复杂度,根据最优归一化因子的变化特征,对其采用加权平均处理;为了降低平均迭代次数,加快译码的收敛速度,所提算法利用校验节点信息的残差特性进行分层处理,优先更新残差值较大的一层,在不同迭代之间动态地重新排列层。仿真结果表明,提出的RB_LINMS译码算法,在误比特率为10-5时,相比于传统的NMS算法,其译码性能可获得0.26 d B的增益,平均迭代次数最多能够降低33.20%。因此,在复杂度略有增加的情况下,能够实现更快的收敛速度和出色的译码性能。

基于阿贝尔群上的差分集构造LDPC码

本文给出了区组长度为3、4和5的平衡不完全区组设计,将设计的关联矩阵作为校验矩阵,从而构造出3种低密度奇偶校验码(LDPC,low-density parity-check code)。由于这些校验矩阵是准循环矩阵,所以构造的码是拟循环LDPC码(QC-LDPC,quasi-cyclic LDPC)。计算码的相关参数,并针对具体的例子通过与类随机码的译码性能进行分析比较,结果显示,所构造的码具有较好的性能。

天基信息传输高效低复杂度LDPC译码算法研究

军事卫星通信由于需满足信息实时性、传输速率高、通信容量大以及符合星间链路信道的时变特性等要求,通常采用高编码增益、高吞吐量的信道编码方案。低密度奇偶校验(Low-Density Parity-Check,LDPC)码由于具备接近Shannon极限的优异纠错性能和可并行计算的特性成为卫星通信主导信道编码标准之一。目前卫星通信接收机的译码器模块设计仍存在诸如无法实时在线判断迭代停止、系统吞吐量受限、大量判决电路影响核心译码电路的低功耗和实时性等问题。考虑上述问题,以因子图模型为基础,针对空间数据系统咨询委员会(Consultative Committee for Space Data Systems,CCSDS)标准深空通信码型,将校验节点归一化满足概率进化图案与LDPC译码器状态紧密耦合,给出可实时在线判断迭代停止的最优停止准则,实现高性能、低复杂度的停止准则译码算法设计。当优先考虑高吞吐量时,误码率(Bit Error Rate,BER)性能退化0.13 dB,中低信噪比平均迭代次数(Average Number of Iteration,ANI)降低50%以上;当优先考虑纠错性能时,BER性能仅退化0.02 dB,同时大幅降低ANI。该译码算法为高效低复杂度LDPC译码器设计提供有效解决方案。

面向流式通信的耦合LDPC码研究综述

流式通信是光纤通信网络和移动通信网络中重要的通信场景,区别于传统的间歇式或分块通信场景,流式通信中传输的数据具有典型的连续流式特性.面向流式通信场景,耦合码因其相对于传统分组码具有显著的性能提升,加之其天然的低编译码时延结构,成为流式通信场景中重要的信道编码候选技术.本文先回顾现有的耦合低密度校验(Low-Density Parity-Check,LDPC)码技术,包括:乘积类耦合LDPC码、部分重编码类耦合LDPC码、空间耦合LDPC码和全局耦合LDPC码.在此基础上,本文进一步介绍了基于便车码技术的耦合LDPC码改进提升设计,并介绍了基于分组马尔可夫叠加传输技术的一类新型耦合LDPC码.最后,本文对耦合LDPC码的发展前景和研究方向进行展望.

无小环大列重QC-LDPC短码的显式构造

针对列重较大的无4环且无6环的准循环(Quasi-Cyclic,QC)低密度奇偶校验(Low-Density Parity-Check,LDPC)码,本文提出了三种新的显式构造方法.新方法的指数矩阵由两个整数序列完全定义,其中第一个序列是从0开始且公差为1的等差序列,第二个序列是由符合最大公约数约束的整数组成的特殊序列.对于现有显式方法只能提供较大循环块尺寸的多种行重类型,新显式构造方法在这些行重类型下均获得了相当小的循环块尺寸,从而将最小循环块尺寸降低到大约只有原来的一半.与近期提出的基于搜索的对称结构法相比,新的显式构造方法具有类似或更优的译码性能、极低的描述复杂度且不需要计算机搜索.

High Robust Broadcasting over DTMB-A with Low-rate LDPC Codes

As the 2nd generation digital terrestrial television broadcasting(DTTB)standard,digital terrestrial/television multimedia broadcasting-advanced(DTMB-A)can provide higher spectrum efficiency and transmission reliability by adopting flexible frame structure and advanced forward error correction coding compared with the 1 st generation DTTB systems.In order to increase the flexibility and robustness of the DTTB network,the frequency reuse scheme of factor one(reuse-1)is proposed,where the same RF channel is used by different stations covering the adjacent service areas.However,it demands a very low carrier-tonoise ratio(C/N)threshold below 0 dB at the DTTB physical layer.In this paper,a robust broadcasting technique is proposed based on DTMB-A with newly designed low-rate low density parity check(LDPC)codes.By adopting quasi-cyclic(QC)Raptor-like structure and progressive lifting method,the high performance low-rate LDPC codes are designed supporting multiple code lengths.Both density-evolution analyses and laboratory measurements demonstrate that DTMB-A with low-rate coding can complete the demodulation reliably with the C/N threshold below0 d B,which is one important necessary condition to support frequency reuse-1 scheme.

相关噪声下基于深度学习的LDPC码联合降噪译码算法设计

为了改善采用低密度奇偶校验(LDPC)码和高阶调制的无线通信系统在相关噪声下的译码性能,提出了一种联合优化降噪和译码的深度学习算法。降噪器中采用了残余收缩模块(RSBU),译码器采用了基于循环神经网络的神经网络最小和译码算法。在提出的联合降噪译码(JDD)算法中,利用复数神经网络在处理复信号方面比实数神经网络更有优势的特点,提出了一个复数RSCNN(CRSCNN),接收的复信号直接输入CRSCNN并利用新颖的联合优化降噪损失函数和译码损失函数的多任务学习策略来改善译码性能。仿真结果显示基于CRSCNN的JDD算法获得了比基于循环神经网络的神经网络最小和译码算法更好的译码性能。

一种非二进制LDPC与SCMA系统的联合检测译码方案

针对现有的一些低密度奇偶校验码(low-density parity code,LDPC)与稀疏码多址(sparse code multiple access,SCMA)系统联合检测方案复杂度高、误码率高、传输时延大、收敛速度慢的问题,提出一个非二进制低密度奇偶校验码(non-binary lowdensity parity code,NB-LDPC)与SCMA系统的联合检测译码(joint detection decoding,JDD)方案。在SCMA多用户检测部分改进基于阈值辅助的期望传播算法(expect propagation algorithm,EPA),在LDPC部分采用NB-LDPC并且在两节点更新过程选取部分消息状态值来改进译码算法,同时,利用联合因子图在联合检测译码信息交互时加入一种消息阻尼因子来提高收敛速度,最终完成联合检测译码过程。通过多角度仿真发现,该方案降低了复杂度和误码率,减小了传输时延,提高了收敛速度,并且在不同码本下均验证了所提方案的适用性。

基于LDPC码的分布式信源编码的研究

传统的分布式信源编码在城域量子通信中有高误码率和低压缩率的缺点,因此提出一种改进的分布式信源编码算法,在信源译码器的设计中,冗余技术用于纠错检错,基于边信息的和冗余相结合的低密度奇偶校验码设计分布式信源编码。实验表明:这种改进的分布式信源编码算法可以保持高压缩率,并在城域量子通信中系统的内部相关性强时更易于实现。

基于边信息和LDPC的分布式信源编码

传统的分布式信源编码在城域量子通信中有高误码率和低压缩率的缺点,提出了一种改进的分布式信源编码算法,在信源译码器的设计中冗余技术用于纠错检错,基于边信息的和冗余相结合的低密度奇偶校验码设计分布式信源编码.实验表明提出的算法可以保持高压缩率,并在城域量子通信中系统的内部相关性强时更易于实现.

基于双序列反序的(4,L)规则girth-8 QC-LDPC短码

围长较大的短码长准循环(QC)低密度奇偶校验(LDPC)码的显式构造对于QC-LDPC短码的理论研究与工程应用具有重要意义。首先提出一种基于成对策略的贪婪搜索算法,并根据此算法在列重J为4时的经验结果,归纳总结出一种具有双序列反序特征的指数矩阵。随后证明了该指数矩阵对于任意行重L均对应于围长为8的QC-LDPC码。与现有的典型显式构造方法即最大公约数(GCD)方法相比,新QC-LDPC码提供的码长显著降低。最后,将指数矩阵的拆分拼接和掩膜处理技巧与新QC-LDPC码结合起来,设计出了译码性能在高信噪比区超过5G NR LDPC码的合成码。