LDPC码在非相干BFSK系统中的性能分析

通过理论分析和计算机仿真研究了LDPC码在非相干BFSK系统中的性能.首先证明单输入双输出的非相干BFSK系统满足信道对称条件,然后分别利用离散密度进化(DDE)和高斯近似(GA)算法给出了LDPC码的性能下界,后者与前者相比性能非常接近而且计算量要小很多.通过仿真得到几种常用LDPC码的性能并与译码门限以及香农极限进...     

解码前传半双工中继信道下协作LDPC码设计

为逼近解码前传半双工中继信道容量,该文提出一种协作LDPC编码结构及度分布优化方法。与双层删除LDPC码不同,该结构将中继校验比特视为协作LDPC码的一部分,目的端利用从信源和中继接收的消息进行联合译码获得信源信息。为了分析协作LDPC码性能,拓展传统外信息转移(EXIT)图,推导了基于消息错误概率的双层EXIT图噪声门限分析方法。在此基础上,提出了协作LDPC码度分布优化方法,采用差分进化算法搜索了一组具有最大噪声门限的协作LDPC码。实验仿真证明,与双层删除LDPC码相比,协作LDPC码的性能得到了不同程度的改善。     

非规则LDPC度分布优化设计

一对好的度分布可以有效降低LDPC的错误平层和编译码复杂度,在AWGN信道下,通过高斯近似分析方法可近似计算给定度分布的LDPC译码门限,利用差分进化算法可优化度分布以获得具有最大门限的度分布,仿真结果表明获得的度分布的译码门限比线性算法优化结果要好0.15dB左右。     

不规则LDPC码度分布的优化设计研究

针对非规则LDPC码的度分布优化,研究了差分进化算法,并利用差分进化算法得到了最大门限的度分布序列,同时在AWGN信道下,通过高斯近似方法得到了在该度分布对下的较精确的LDPC译码门限。通过仿真发现,在改进后的优化算法中的度分布对得到了更高的门限值。同时高斯近似还能应用到其他高效纠错码,对现代高效纠错码具有重要的指导意义。     

Optimization Design of Degree Distributions for Irregular LDPC Codes

针对非规则LDPC码的度分布优化,研究了差分进化算法,并利用差分进化算法得到了最大门限的度分布序列,同时在AWGN信道下,通过高斯近似方法得到了在该度分布对下的较精确的LDPC译码门限.通过仿真发现,在改进后的优化算法中的度分布对得到了更高的门限值.同时高斯近似还能应用到其他高效纠错码,对现代高效纠错码具有重要的指导意义.     

高阶调制系统下LDPC码优化设计

为了提高编码调制系统的整体编码增益,提出一种高阶调制系统下LDPC码的度分布优化方法.根据高阶调制符号中不同比特的误比特特性,将调制符号所经历信道建模为一组对称二进制输入加性高斯信道.在此基础上,推导了高阶调制系统下LDPC码高斯近似密度进化分析方法,并得到译码收敛条件.结合度分布约束关系及译码收敛条件,提出高阶调制系统下LDPC码的度分布优化问题及差分进化实现方法.仿真结果表明,设计的LDPC码在高阶调制系统中的渐进性能和误码性能优于基于比特优化映射的编码调制方案.     

IRA码密度进化方法分析与门限判决

针对IRA(非规则重复累积)码的和积译码算法,深入研究了其密度进化方法的原理,并推导了2种密度进化实现算法,即IRA码的离散密度进化和高斯近似算法。在AWGN(加性高斯白噪声)信道中利用2种算法对DVB-S2标准中的IRA码进行门限判决,并对其中的一类码的译码性能进行仿真,为研究和应用DVB-S2标准提供了参考数据。     

非正则LDPC码在DSP上的实现

首先简单介绍了非正则LDPC码的结构,给出了一种基于IEEE802.16e直接编码法生成的(576,288)非正则LDPC码的编译码原理。然后详细论述了其在TI定点DSP(TMS320C5510)上的定点化算法实现方式,并在经过C和部分汇编优化后将算法效率提高了70%以上,达到了实时系统要求。最后给出了该LDPC码与(2,1,7)卷积码在AWGN信道下的性能对比,表明这种中短码长的非正则LDPC码较卷积码有较大的纠错性能优势。     

删余低密度奇偶校验码的分析与设计

通信系统中在不同的信道条件下常采用不同的编码速率,删余码是实现这种策略的有效方式。该文基于高斯近似思想,分析了高斯白噪声信道上删余LDPC码的消息传递译码算法,并在推导出消息均值迭代公式的基础上提出了一种优化删余分布的方法。仿真结果表明,根据此优化方法设计的删余LDPC码在消息传递译码算法下,消息均值增长较快并且消息传递译码算法具有较快的收敛速度。     

基于差分进化的非规则LDPC码分布对优化

讨论了基于差分进化的非规则LDPC码分布对优化方法。在分布对的优化搜索过程当中,联合使用了差分进化算法(EA)与密度进化算法,并对这种联合技术的实现方法和约束条件处理做了研究。用密度进化算法作为差分进化算法的目标函数,优化搜索出了一组AWGN信道下好的非规则LDPC码分布对,且计算出了各分布对的近似门限值。该方法充分利用差分进化算法的健壮性、有效性以及搜索结果全局最优的特点,是一种有效的好LDPC码搜索技术。     

快衰落Rayleigh信道下短LDPC码两类BP-Based译码的优化设计

该文基于最小均方误差(MMSE)准则,对快衰落瑞利(Rayleigh)信道下短码长低密度校验(LDPC)码的Scaled BP-Based和Offset BP-Based两类改进译码算法进行了优化设计。利用该准则,得出了两类改进算法的最优校正因子,并给出了相应的数值计算。对码长为504和1008的1/2码率(3,6)规则LDPC码实验仿真显示,使用该准则设计的两类算法能够取得优于置信传播(BP)算法的译码性能。     

Density evolution for two improved BP-Based decoding algorithms ofLDPC codes

In this letter, we analyze the performance of two improved belief propagation (BP) based decoding algorithms for LDPC codes, namely the normalized BP-based and the offset BP-based algorithms, by means of density evolution. The numerical calculations show that with one properly chosen parameter for each of these two improved BP-based algorithms, performances very close to that of the BP algorithm can be achieved. Simulation results for LDPC codes with code length moderately long validate the proposed optimization     

Performance analysis and code optimization of low densityparity-check codes on Rayleigh fading channels

A numerical method has been presented to determine the noise thresholds of low density parity-check (LDPC) codes that employ the message passing decoding algorithm on the additive white Gaussian noise (AWGN) channel. In this paper, we apply the technique to the uncorrelated flat Rayleigh fading channel. Using a nonlinear code optimization technique, we optimize irregular LDPC codes for such a channel. The thresholds of the optimized irregular LDPC codes are very close to the Shannon limit for this channel. For example, at rate one-half, the optimized irregular LDPC code has a threshold only 0.07 dB away from the capacity of the channel. Furthermore, we compare simulated performance of the optimized irregular LDPC codes and turbo codes on a land mobile channel, and the results indicate that at a block size of 3072, irregular LDPC codes can outperform turbo codes over a wide range of mobile speeds     

Hybrid Hard-Decision Iterative Decoding of Irregular Low-Density Parity-Check Codes

Time-invariant hybrid (Hscr_TI) decoding of irregular low-density parity-check (LDPC) codes is studied. Focusing on Hscr_TI algorithms with majority-based (MB) binary message-passing constituents, we use density evolution (DE) and finite-length simulation to analyze the performance and the convergence properties of these algorithms over (memoryless) binary symmetric channels. To apply DE, we generalize degree distributions to have the irregularity of both the code and the decoding algorithm embedded in them. A tight upper bound on the threshold of MB Hscr_TI algorithms is derived, and it is proven that the asymptotic error probability for these algorithms tends to zero, at least exponentially, with the number of iterations. We devise optimal MB Hscr_TI algorithms for irregular LDPC codes, and show that these algorithms outperform Gallager's algorithm A applied to optimized irregular LDPC codes. We also show that compared to switch-type algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different MB algorithms, MB Hscr_TI algorithms are more robust and can better cope with unknown channel conditions, and thus can be practically more attractive     

Accumulate-Repeat-Accumulate Codes

In this paper, we propose an innovative channel coding scheme called accumulate-repeat-accumulate (ARA) codes. This class of codes can be viewed as serial turbo-like codes or as a subclass of low-density parity check (LDPC) codes, and they have a projected graph or protograph representation; this allows for high-speed iterative decoding implementation using belief propagation. An ARA code can be viewed as precoded repeat accumulate (RA) code with puncturing or as precoded irregular repeat accumulate (IRA) code, where simply an accumulator is chosen as the precoder. The amount of performance improvement due to the precoder will be called precoding gain. Using density evolution on their associated protographs, we find some rate-1/2 ARA codes, with a maximum variable node degree of 5 for which a minimum bit SNR as low as 0.08 dB from channel capacity threshold is achieved as the block size goes to infinity. Such a low threshold cannot be achieved by RA, IRA, or unstructured irregular LDPC codes with the same constraint on the maximum variable node degree. Furthermore, by puncturing the inner accumulator, we can construct families of higher rate ARA codes with thresholds that stay close to their respective channel capacity thresholds uniformly. Iterative decoding simulation results are provided and compared with turbo codes. In addition to iterative decoding analysis, we analyzed the performance of ARA codes with maximum-likelihood (ML) decoding. By obtaining the weight distribution of these codes and through existing tightest bounds we have shown that the ML SNR threshold of ARA codes also approaches very closely to that of random codes. These codes have better interleaving gain than turbo codes     

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.     

Analysis of sum-product decoding of low-density parity-check codesusing a Gaussian approximation

Density evolution is an algorithm for computing the capacity of low-density parity-check (LDPC) codes under message-passing decoding. For memoryless binary-input continuous-output additive white Gaussian noise (AWGN) channels and sum-product decoders, we use a Gaussian approximation for message densities under density evolution to simplify the analysis of the decoding algorithm. We convert the infinite-dimensional problem of iteratively calculating message densities, which is needed to find the exact threshold, to a one-dimensional problem of updating the means of the Gaussian densities. This simplification not only allows us to calculate the threshold quickly and to understand the behavior of the decoder better, but also makes it easier to design good irregular LDPC codes for AWGN channels. For various regular LDPC codes we have examined, thresholds can be estimated within 0.1 dB of the exact value. For rates between 0.5 and 0.9, codes designed using the Gaussian approximation perform within 0.02 dB of the best performing codes found so far by using density evolution when the maximum variable degree is 10. We show that by using the Gaussian approximation, we can visualize the sum-product decoding algorithm. We also show that the optimization of degree distributions can be understood and done graphically using the visualization     

Analysis of stability condition for LDPC codes and optimizing degree sequences over mixed channel

Under the circumstance that white Gaussian noise and random erasures exist all at once,the stability condition for LDPC codes over mixed channel was proposed.And it was proved that a good degree sequence of LDPC codes was not optimized over mixed channel.It can also be proved by simulation.The random particle swarm optimization (RPSO) and simulated annealing (SA) algorithm were combined to find some capacity-approaching degree sequences over mixed channel with different erasure probabilities.The threshold of signal-to-noise ratio improves 1.615 9 dB than that of the classical degree sequences calculated by Gaussian approximation over mixed channel.These degree sequences are optimal for optical recording and frequency-hopping communication with narrow-band interference.