一种改进的Turbo乘积码译码算法

针对Turbo乘积码(TPC)译码复杂度高、运算量大的缺点,分析了一种改进的TPC译码算法。该算法以Chase迭代算法为基础,通过对错误图样重新排序产生新的测试序列,其伴随式可从前次伴随式的基础上修正一位得到,大大简化了计算步骤。在AWGN信道下对新算法进行了Matlab仿真,结果表明,改进的算法在保持译码性能基本不变的前提下,提高了译码速度,降低了译码复杂度。     

Turbo乘积码梯度译码算法研究

Turbo乘积码(简称TPC码)是一类采用简单的行列交织器将分组码进行串行级联而构成的纠错码.文中针对二进制turbo乘积码提出了一种快速的软判决译码算法一梯度译码算法.该算法是以迭代Chase算法为基础,通过利用chase算法上次迭代译码而得到的每行(或列)最优判决码D(m-1)来代替竞争码字C,节省了寻找C的过程,从而简化了外信息和软输出的计算.仿真结果表明:梯度算法能在基本保持turbo乘积码的Chase算法译码性能基础上,提高了译码速度,降低了译码复杂度.     

Turbo乘积码在无人机测控技术中的应用分析

Turbo乘积码是一种易于硬件实现的分组码,具有延时短和纠错性能好等优越性。通过对Turbo乘积码Chase软输出改进算法的分析和仿真,得出了不同码率和测试序列个数等参数对Turbo乘积码译码性能的影响。结合无人机常用的BPSK测控信号进行了仿真实验,对仿真结果进行了性能分析,验证了Turbo乘积码在无人机测控系统中应用的可行性,并给出了Turbo乘积码在无人机测控领域应用的建议参数。     

乘积码迭代译码算法研究

介绍了在分组码的软输入软输出译码基础上以扩展BCH码为子码的乘积码的迭代译码算法,提出了在高带宽利用率调制方式下的算法应用方式,并给出了仿真结果。最后与传统的并联卷级码代译码方案比较,发现在高编码效率时,乘积码迭代译码方案有着较好的应用性。     

基于VHDL的TPC译码器设计

Turbo乘积码是一种性能卓越的前向纠错码,具有译码复杂度低,且在低信噪比时可以获得近似最优的性能。介绍基于Chase算法的Turbo乘积码软入软出（SISO）迭代译码算法,提出基于VHDL硬件描述语言的TPC译码器设计方案,并在FPGA芯片上进行了仿真和验证。仿真结果证明该译码器有很大的实用性和灵活性。     

Turbo乘积码译码算法的简化

Chase算法是Turbo乘积码(TPC)软判决译码中常采用的算法之一。分析了传统Chase算法中寻找竞争码字对译码复杂度的影响,在此基础上提出了两种新的简化译码算法,省去了寻找竞争码字的过程。仿真结果表明,简化算法在基本保持传统Chase算法译码性能的基础上,降低了译码复杂度,提高了译码速度。     

高速通信系统中两种Turbo迭代译码算法的比较

1993年提出的Turbo码因其优异的性能而引起编码界的关注.之后不久提出的乘积码,是Turbo码的一个分支,他是一种分组纠错码,具有良好的性能.但是多年来大多数学者将研究集中于卷积Turbo码,而很少有人关注考虑分组Turbo码（即乘积码）,事实上乘积码相比卷积Turbo码在牺牲较小性能的情况下很大程度地降低了译码复杂度.本文将基于软输入/输出的Turbo译码算法,提出并分析了传统的卷积Turbo码和分组Turbo码（乘积码）的迭代译码算法,并对比分析了两者的译码性能,最后结果表明,两类码非常适合于未来的高速移动通信系统应用,尤其对乘积码,不仅具有较高的码率,同时可以获得更好的误比特率性能,在实际应用中更具有吸引力.     

软输入/软输出迭代译码算法的研究与设计

对软输入/软输出迭代译码算法进行了理论研究,分析该算法的共性,并以Turbo 乘积码的性能仿真说明迭代译码对译码性能的影响,还以理论研究为基础,对迭代译码算法进行了硬件设计,重点探讨了Turbo 乘积码的译码算法硬件设计.     

迭代译码的级联Reed-Solomon乘积码与卷积码

该文提出用Reed Solomon(RS)乘积码作为外码,卷积码作为内码的级联码方案并且内外码间用Congruential向量生成的交织图案对RS码符号进行重排列。对此级联码采用的迭代译码基于成员码的软译码算法。当迭代次数达到最大后,通过计算RS码的校正子,提出一种纠正残余错误的方法,进一步提高了系统的误比特性能。仿真结果表明,在AWGN信道中与迭代译码的级联RS/卷积码相比,当误比特率为1e-5时,新系统的编码增益大约有0.4 dB。     

一种乘积码译码器设计方案的研究

介绍了一种乘积码迭代译码器的硬件设计方案。基于软判决译码规则,使用VHDL硬件描述语言,提出了基于Modelsim6.Oa仿真平台的两维乘积码的EDA实现方法,给出了仿真波形,迭代次数为四次时最大译码速率可达到50Mbit/s,并通过了在Xilinx公司的FPGA芯片XC2S200上的综合验证实验。该译码器的功能仿真和硬件实现都证明了这种方案的可行性和正确性。     

Systematic redundant residue number system codes: analytical upper bound and iterative decoding performance over AWGN and Rayleigh channels

The novel family of redundant residue number system (RRNS) codes is studied. RRNS codes constitute maximum-minimum distance block codes, exhibiting identical distance properties to Reed-Solomon codes. Binary to RRNS symbol-mapping methods are proposed, in order to implement both systematic and nonsystematic RRNS codes. Furthermore, the upper-bound performance of systematic RRNS codes is investigated, when maximum-likelihood (ML) soft decoding is invoked. The classic Chase algorithm achieving near-ML soft decoding is introduced for the first time for RRNS codes, in order to decrease the complexity of the ML soft decoding. Furthermore, the modified Chase algorithm is employed to accept soft inputs, as well as to provide soft outputs, assisting in the turbo decoding of RRNS codes by using the soft-input/soft-output Chase algorithm.     

On algebraic soft-decision decoding algorithms for BCH codes

Three algebraic soft-decision decoding algorithms are presented for binary Bose-Chaudhuri-Hocquengham (BCH) codes. Two of these algorithms are based on the bounded distance (BD)+1 generalized minimum-distance (GMD) decoding presented by Berlekamp (1984), and the other is based on Chase (1972) decoding. A simple algebraic algorithm is first introduced, and it forms a common basis for the decoding algorithms presented. Next, efficient BD+1 GMD and BD+2 GMD decoding algorithms are presented. It is shown that, for binary BCH codes with odd designed-minimum-distance d and length n, both the BD+1 GMD and the BD+2 GMD decoding algorithms can be performed with complexity O(nd). The error performance of these decoding algorithms is shown to be significantly superior to that of conventional GMD decoding by computer simulation. Finally, an efficient algorithm is presented for Chase decoding of binary BCH codes. Like a one-pass GMD decoding algorithm, this algorithm produces all necessary error-locator polynomials for Chase decoding in one run     

Pattern-Flipping Chase-Type Decoders with Error Pattern Extracting Viterbi Algorithm over Partial Response Channels

Towards the goal of achieving better error correction performance in data storage systems, iterative soft decoding of low density parity check (LDPC) codes and soft-decision decoding of Reed-Solomon (RS) codes have started receiving increasing research attention. However, even with increased computing power, complexities of soft-decision decoding algorithms are still too high for real products which require high throughput and small hardware area. Another problem is that the performance gains of those approaches are smaller for magnetic recording channels than they are for memoryless additive white Gaussian noise (AWGN) channels. We propose a new soft-decision decoding algorithm (based on the Chase algorithm), which takes advantage of pattern reliability instead of symbol reliability or bit reliability. We also present a modified Viterbi algorithm that provides probable error patterns with corresponding reliabilities. Simulation results of the proposed algorithms over the partial response (PR) channel show attractive performance gains. The proposed algorithm dramatically reduces the number of iterations compared to the conventional Chase2 algorithm over the PR channel.     

一种基于Chase的RS码代数软判决译码算法

为了提高RS码的纠错性能,本文提出了一种基于Chase的代数软判决译码算法,称为Chase-ASD.该算法充分利用了接收比特的可信度信息,但运算复杂度较高.针对该算法运算复杂度高的问题,本文进一步给出了简化的Chase-ASD算法.仿真结果表明,提出的Chase-ASD和简化的Chase-ASD算法均可比原ASD算法提供更多的译码增益.     

一种改进的二阶Reed-Muller译码算法

研究了一种改进的RM译码算法—改进的Sidel,nikov-Pershakov算法(简称SP算法),详细叙述了原始算法的原理以及改进算法的译码步骤,并对两种算法进行了仿真实现,对它们的译码性能和算法复杂度进行了比较。改进的译码算法复杂度略优于原始算法,而改进后的算法的译码性能明显优于原始算法。     

基于改进型SOVA的Turbo译码

第三代移动通信系统IMT-2000的高速率业务倾向于选择Turbo码,这就要求采用低时延、低复杂度的迭代译码技术,主要是软输出Viterbi算法(SOVA)和Max-Log-MAP算法.在先验等概和无限译码深度条件下,已证明略加修改的SOVA等效于Max-Log-MAP算法.由于在迭代译码中,先验概率须不断更新,本文证明了在存在先验概率的条件下改进型SOVA与Max-Log-MAP也是等效的,并讨论了有限译码深度限制下改进型SOVA与滑动窗口Max-Log-MAP算法的等效性.     

用可变的软距离门限改进Chase2算法

本文计算了用Chase2算法不可捕获的错误图样的软重量的下限,由此证明了当接收序列到某个码字的软判决距离满足王新梅(1986)提出的广义门限时,该算法与最大似然译码有相同的译码结果。又进一步得出了随接收序列可信度变化的可变门限,可以用来加快软判决译码的速度而不损失译码性能。     

Near-optimum decoding of product codes: block turbo codes

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is an estimation of the log-likelihood ratio (LLR) of the binary decisions given by the Chase decoder. The theoretical justifications of this algorithm are developed and the method used for computing the soft output is fully described. The iterative decoding of product codes is also known as the block turbo code (BTC) because the concept is quite similar to turbo codes based on iterative decoding of concatenated recursive convolutional codes. The performance of different Bose-Chaudhuri-Hocquenghem (BCH)-BTCs are given for the Gaussian and the Rayleigh channel. Performance on the Gaussian channel indicates that data transmission at 0.8 dB of Shannon's limit or more than 98% (R/C>0.98) of channel capacity can be achieved with high-code-rate BTC using only four iterations. For the Rayleigh channel, the slope of the bit-error rate (BER) curve is as steep as for the Gaussian channel without using channel state information