深空通信中的线性Log-MAP算法

Turbo码由于具有逼近香农信道容量限的性能,已经被CCSDS标准采纳。译码算法是Turbo码译码的关键组成部分,也是影响其性能的关键因素,而MAP类译码算法以其优越的性能成为译码算法的主体。在对MAP类译码算法的译码复杂度和性能仿真对比、分析的基础上,针对深空通信中的低信噪比、低误比特率的要求,提出一种线性Log-MAP算法方案,该方案在保证性能损失尽可能小的前提下,有效降低了计算复杂度,适用于深空通信的实际要求。     

MAP译码器的免归一化处理信息更新算法

在不改变译码性能的条件下,为了加快最大后验概率(Maximum A Posteriori Probability,MAP)译码器状态信息更新的速度和降低算法的复杂度,提出了一种用于Turbo码的MAP译码器的免归一化处理算法.算法采用二进制补码加法器和减法器将MAP译码过程中的状态信息投影到一个归一化圆上,当状态信息更新时所有的状态信息在归一化圆上移动,通过保持归一化圆上状态信息的正确关系来计算似然比.归一化过程中不用搜索或估计状态信息的最大值,通过简化状态信息归一化过程加速了MAP译码器的状态信息更新并降低了复杂度.所提算法在与传统算法译码性能相同的情况下,可以降低36.2％的计算复杂度和17.4％的关键路径延迟,达到MAP译码器实现中的高速、低复杂度目标.     

MIMO-OFDM中基于KSDA和SQRD的联合检测算法

球形译码算法的检测性能最接近最大似然检测算法,但其计算复杂度仍然较高。为了在计算复杂度和系统性能之间取得良好折中,在研究标准球形译码的基础上,提出一种新的球形译码改进算法。新算法由快速球形译码与基于MMSE准则的SQRD算法构成。该算法在高信噪比时采用SQRD算法,低信噪比时采用KSDA算法。仿真结果表明,该算法在降低球形译码算法复杂度的同时获得了较好的系统性能。     

累加交叉并行级联单奇偶校验码的低复杂度译码算法

累加交叉并行级联单奇偶校验(A-CPSPC)码是一种新的纠错编码,其编码结构简单并具有较好的误比特率性能。该文针对A-CPSPC码的局部编码结构提出了一种低复杂度的最大后验(MAP)局部译码算法,该方法利用基于双向消息传递原则的和积算法(SPA)进行局部译码,消除了短环对局部译码性能的影响。分析及仿真表明,传统的置信传播算法并不适用于A-CPSPC码,该文提出的局部译码算法与基于BCJR算法的局部译码算法的性能一致,且复杂度更低。     

一种新的LDPC译码算法

由于LDPC码的优良性能,因此在信息可靠传输中有良好的应用前景。本文提出了一种将BP算法和基于列表的SIHO(软输入硬输出)算法相结合的译码算法,通过与BP、MLD算法的误码率性能和译码复杂度比较,本算法复杂度比MLD有明显降低,而在性能上优于BP算法并接近MLD译码算法。     

极化码序列连续删除译码算法的改进设计

极化码连续删除译码算法性能和传统的LDPC码存在一定差距。序列连续删除算法(SCL)的提出极大地改善译码性能,是极化码推向实际应用中的重要一步。但是该算法复杂度较高,延迟大。改进的序列连续删除(SCL)译码算法是基于改善极化码码长受限的情况,文中描述SCL算法是通过码树上的搜索序列路径来表示译码过程。改进的算法通过减少译码算法在码树上的序列路径来降低时间和空间复杂度。通过仿真表明,改进的算法有效地降低了译码的复杂度同时在性能上也接近最大似然(ML)译码算法。     

LTE-A系统一种降低复杂度的软球形检测算法

软球形译码算法虽然能接近ML(最大似然)算法的误码性能,但其计算复杂度很高。文章提出了一种降低计算复杂度的SSD(软球形译码)算法,该算法在QR(正交三角)分解算法的反向迭代上三角矩阵R中引入减弱噪声部分以缩小初始搜索半径,然后利用最小距离准则对搜索树进行有效地删减,缩小树搜索空间。MATLAB仿真结果表明,该算法在获得接近传统SSD性能的条件下,能够很大程度地降低系统的计算复杂度。     

基于变量节点更新改进的最小和算法

LDPC码是一种具有稀疏性且接近香农极限的线性分组码。目前被广泛应用的LDPC简化算法的译码性能损失较多,译码性能和复杂度折中的算法具有重要价值。对几种已知的译码算法进行了深入研究,提出一种基于变量节点更新改进的最小和算法,该算法与最小和算法、归一化最小和算法复杂度相当,但译码性能得到约0.5 d B和0.2 d B的提高,在中高信噪比区,更加接近LLR-BP算法的性能。     

基于SCCC结构非相干MAP译码的简化算法

差分编码和序列译码相结合是实现高性能非相干解调的主要方式。对采用差分编码的SCCC结构进行非相干译码,其性能近乎于相干解调,但在估计信道转移概率时引入了修正的零阶贝塞尔函数,因此译码复杂度过高,不利于工程实现。针对该问题,该文提出了两种基于SCCC结构的非相干MAP译码的简化算法。该算法利用对贝塞尔函数的近似式,简化了内码译码log-MAP算法中分支度量的计算。理论分析和仿真结果表明,简化后的算法在保证译码性能的前提下,显著地减小了译码复杂度。     

分组码的软判决伪序列译码

本文提出一种在形式上类似于卷积码的序列译码的一般线性分组码的软判决伪序列译码算法，利用广义限译码原理及二元有向树的性质与分枝限搜索技术，降低了译码复杂性，其设备复杂度小于Ｃｈａｓｅ译码器，模拟结果表明，该算法的误码输出性能接近维持比较最大似然译码，好于ＣｈａｓｅⅡ算法，且译码速度与ＣｈａｓｅⅡ算法接近。     

MAP algorithms for decoding linear block codes based onsectionalized trellis diagrams

The maximum a posterioriprobability (MAP) algorithm is a trellis-based MAP decoding algorithm. It is the heart of turbo (or iterative) decoding that achieves an error performance near the Shannon limit. Unfortunately, the implementation of this algorithm requires large computation and storage. Furthermore, its forward and backward recursions result in a long decoding delay. For practical applications, this decoding algorithm must be simplifled and its decoding complexity and delay must be reduced. In this paper, the MAP algorithm and its variation's, such as log-MAP and max-log-MAP algorithms, are first applied to sectionalized trellises for linear block codes and carried out as two-stage decodings. Using the structural properties of properly sectionalized trellises, the decoding complexity and delay of the MAP algorithms can be reduced. Computation-wise optimum sectionalizations of a trellis for MAP algorithms are investigated. Also presented in this paper are bidirectional and parallel MAP decodings     

Turbo码的一种全新的SOVA译码算法

SOVA算法因其译码时延低于MAP算法已成为Turbo码的实用译码算法。本文提出了一种放弃软判决值更新处理的全新的SOVA算法。该算法的独到之处在于,综合利用对栅格图的正向和反向搜索,从而实现了通过全局路径比较来产生软输出值。仿真结果表明,与传统SOVA算法相比这种全新的SOVA算法在不会明显增加译码计算量的前提下,显著地改善了译码性能。同时,其误码率性能在高信噪比时略优于Max-Log-MAP算法,并且已经逼近MAP算法。     

High-Speed Recursion Architectures for MAP-Based Turbo Decoders

The maximum a posterior probability (MAP) algorithm has been widely used in Turbo decoding for its outstanding performance. However, it is very challenging to design high-speed MAP decoders because of inherent recursive computations. This paper presents two novel high-speed recursion architectures for MAP-based Turbo decoders. Algorithmic transformation, approximation, and architectural optimization are incorporated in the proposed designs to reduce the critical path. Simulations show that neither of the proposed designs has observable decoding performance loss compared to the true MAP algorithm when applied in Turbo decoding. Synthesis results show that the proposed Radix-2 recursion architecture can achieve comparable processing speed to that of the state-of-the-art recursion (Radix-4) architecture with significantly lower complexity while the proposed Radix-4 architecture is 32% faster than the best existing design     

A Modified max-log-MAP Decoding Algorithm for Turbo Decoding

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The max-log list algorithm (MLLA)-a list-sequence decoding algorithm that provides soft-symbol output

We present a soft decoding algorithm for convolutional codes that simultaneously yields soft-sequence output, i.e., list sequence (LS) decoding, and soft-symbol output. The max-log list algorithm (MLLA) introduced in this paper provides near-optimum soft-symbol output equal to that of the max-log maximum a posteriori (MAP) probability algorithm. Simultaneously, the algorithm produces an ordered list containing LS-MAP estimates. The MLLA exists in an optimum and a suboptimum version that are different in that the optimum version produces optimum LS-MAP decoding for arbitrary list lengths, while the suboptimum low-complexity version only provides the MAP, the second-order MAP, and the third-order MAP sequence estimates. For lists with more than three elements, MAP decoding is not guaranteed, but the LS decoding is close to the optimal. It is demonstrated that the suboptimum/optimum MLLA can be used to obtain the combination of soft-symbol and soft-sequence outputs at lower complexity than a previously published algorithm. Furthermore, the suboptimum MLLA is well suited for operation in an iterative list (turbo) decoder, since it is obtained by only minor modifications of the well-known Max-Log-MAP algorithm frequently used for decoding of the component codes of turbo codes. Another potential area of application for the suboptimum/optimum MLLA is joint source-channel LS decoding. Estimates of complexity and memory use, as well as performance evaluations of the suboptimum/optimum MLLA, are provided in this paper.     

Modified maximum a posteriori decoding algorithm

A modified maximum a posteriori (MMAP) decoding algorithm that uses two extrinsic information values as the thresholds to determine the log-likelihood ratio, forward recursion probability and backward recursion probability is proposed. The MMAP requires less decoding time and complexity than an MAP decoder. Each probability of the proposed algorithm is derived and compared to that obtained using the MAP algorithm     

一种低复杂度双二元卷积Turbo码译码算法

双二元卷积Turbo码（ DB CTC)的非二进制编码使得译码复杂度增加,限制了其在某些实际通信工程中的使用。在最大后验概率（ MAP)译码算法的基础上,提出了一种优化算法,将译码的存储量和计算量降为原来的1/4。仿真结果表明：在不同编码长度和码率的情况下,优化算法与原算法性能相当;在误码率为10-5的条件下,两者的Eb/N0差异同样不大于0.1 dB。     

Analogue decoding of tail-biting convolutional codes based on tanner graph

A scheme is proposed to decode a tail-biting convolutional code based on its Tanner graph, which is traditionally done using a forward-backward MAP algorithm. Therefore, decoding may be performed using a standard sum-product algorithm. With respect to decoding based on trellis, all variables in a Tanner graph are binary, which may lead to complexity reduction. A min-sum algorithm is used to decrease the analogue circuit complexity. Simulation shows there is no significant degradation compared with more complex traditional methods     

空时分块编码OFDM系统的Turbo均衡

研究了空时分块编码的OFDM（正交频分复用）系统,对系统进行了Turbo均衡,并讨论了此时系统的译码算法和均衡算法。系统信道编码采用Turbo码,通过对BCJR（Bahl,Cocke,Jelinek,Raviv）算法的简单修改得到SISO（单输入单输出）MAP（最大后验概率）译码算法;均衡器采用SISOMMSE（最小均方差）Turbo均衡算法,并利用OFDM系统的循环前缀特性进一步降低算法复杂度。通过仿真对系统性能进行了比较分析,仿真结果表明,采用迭代均衡的空时分块编码OFDM系统性能要明显优于未空时编码和未迭代均衡的OFDM系统。