一种低复杂度咬尾卷积码译码算法﹡

对于咬尾卷积码的译码,传统的最大似然译码算法需要遍历每个可能的起始状态对应的咬尾格形子图,译码复杂度过高.循环维特比算法是一种有效的低复杂度次优译码算法.通过对循环维特比算法中的循环陷阱进行研究,提出了一种新的循环陷阱检测方法,利用对循环陷阱的检测可以减少冗余迭代;同时利用最大似然咬尾路径对非似然起始状态进行排除,极大的缩小了循环维特比算法中译码搜索空间.在此基础上得到了一种低复杂度的译码算法.     

低复杂度的TBCC自适应循环VA译码算法

咬尾是一种将卷积码转换为块码的技术,它消除了归零状态所造成的码率损失,同时避免了截尾带来的性能降低,在短块编码中具有明显优势。针对咬尾卷积码(TBCC)现有译码算法复杂度过大和收敛性问题,提出一种低复杂度的TBCC自适应循环维特比(VA)译码算法。该算法根据信道变化自适应调整译码迭代次数,使咬尾路径收敛到最佳。通过仿真对比不同译码算法的块错误率和译码迭代次数,结果表明TBCC性能明显好于传统卷积码;相比于同类循环VA算法,在不降低性能的前提下,改进算法简化了停止规则,减少译码迭代次数和复杂度,在低信噪比时,改进算法比传统绕维特比译码算法(WAVA)平均迭代次数减少约4次。      

基于Viterbi-双向搜索的咬尾码最大似然译码算法

传统咬尾码最大似然(ML)译码算法在译码时存在两个问题:复杂度高和消耗存储空间大。针对这两个问题,该文提出了一种基于Viterbi算法和双向搜索算法的最大似然译码算法。新算法利用Viterbi算法得到的幸存路径度量值与最大似然咬尾路径度量值的关系,删除不可能的起始状态及其对应的咬尾格形子图,缩小搜索空间;然后利用双向搜索算法中门限值与最大似然咬尾路径度量值的关系来降低双向搜索算法的复杂度,从而得到一种在咬尾格形图上高效率的最大似然译码算法。新的最大似然译码算法不仅降低了译码复杂度,同时降低了译码器对存储空间的需求。     

基于可信位置排序的咬尾卷积码译码算法

咬尾卷积码的传统译码算法没有考虑咬尾格形图的循环性,译码起始位置固定,译码效率相对较低。该文首次证明了咬尾卷积码基于格形图的译码算法与译码起始位置无关,即从任意位置开始译码得到的最优咬尾路径即为全局最优咬尾路径。基于此提出一种基于可信位置排序的咬尾卷积码译码算法。新算法利用咬尾格形图的循环性,根据接收到的信道输出序列估算每个译码起始位置的可靠性,从而选择一个可靠性最高的译码起始位置。和传统译码算法相比,所提算法具有更快的收敛速度。     

一种应用于LTE系统的Viterbi译码算法

LTE(long term evolution,长期演进)系统中采用了咬尾卷积码和Turbo码来实现前向纠错,Viterbi译码是卷积码的一种杰出的译码算法,它是一种最大似然译码方法。本文基于LTE系统中的咬尾卷积码,详细分析了几种较成熟的Viterbi译码算法,并综合现有算法,提出了一种改进算法,减小了译码计算的复杂度。仿真结果表明,改进算法在降低译码计算复杂度的同时还降低了译码误比特率,因此非常适合LTE系统的译码要求。     

列表维特比译码算法在TD-SCDMA中的应用

卷积码在各通信系统中广泛使用,其最大似然(ML)译码算法为维特比译码算法(VA)。传统的维特比译码算法(CVA)仅产生一个最佳译码序列,在低信噪比(SNR)或者恶劣环境下,还是会出现较高概率的误判。为了提高译码性能,列表维特比算法(LVA)被提出,LVA可以同时产生L个候选最优幸存路径,对L个候选最优幸存路径分别进行校验比特验证,从而获得CVA更优的性能。在TD-SCDMA中大部分采用卷积编码的业务,文章将LVA应用到该系统中,并与CVA性能和实现复杂度上对比分析。从仿真结果可以看出,该LVA能提高1dB以上的性能增益。     

TD-LTE系统中咬尾卷积码译码器的FPGA实现

在LTE中,为了获得正确无误的数据传输,要采用差错控制编码技术。LTE中是采用Viterbi和Turbo加速器来实现前向纠错。咬尾卷积码保证格形起始和终止于某个相同的状态,它具有不要求传输任何额外比特的优点。本文提出一种在FPGA中实现的咬尾卷积码的Viterbi译码算法,并在Xilinx的XC3S500E芯片上实现了该算法,最后对该算法性能进行了分析。     

一种改进的快速相关攻击算法

T.Johansson[4]提出了一种基于卷积码维特比(Viterbi)译码方案的快速相关攻击算法。在此基础上, 本文对这个算法进行了改进,提出了一种序列密码的快速相关攻击的改进算法。该改进算法使用了Fano译码方案: 由于它在寻找正确的路径时,力求尽早地排除所有非最大似然路径,这样使译码复杂度比维特比的译码复杂度低, 从而大大地提高了算法攻击成功的速度。     

基于TD-LTE中下行MIMO技术的信号检测算法

MIMO技术是LTE系统中的一个关键技术。在实际应用中,下行MIMO信号检测算法的选用需要在计算复杂度和系统性能之间取得合理的折中。文中对几种传统的检测算法—ML、MMSE、最优排序的SIC算法、QR分解算法、循环迭代QR分解算法进行了分析与研究。经仿真表明,除最大似然算法,循环迭代QR分解算法在这几种算法中性能是最好的。但是从计算复杂度出发,循环迭代QR分解算法远优于最大似然算法。所以,选用循环迭代QR分解算法运用于TD-LTE无线综合测试仪。     

一种针对频率选择性MIMO信道的新型空时分层迭代检测算法

本文针对FS-BLAST算法中的误码扩散问题提出了一种新的分层迭代方法：部分最大似然分层迭代（MLIC）算法。FS-BLAST由于采用了干扰对消的方案,不可避免的产生了误码扩散问题。在本文中,提出了一种新的部分最大似然分层迭代方案,它在分层迭代算法中引入最大似然的概念,是最大似然检测和分层迭代算法的折衷。从实验仿真中,可以看出,这种改进的算法比传统的FS-BLAST和已有的迭代算法具有更好的系统性能。     

A Maximum Likelihood Decoding Algorithm for Wireless Channels

A new maximum likelihood decoding (MLD) algorithm for linear block codes is proposed. The new algorithm uses the algebraic decoder in order to generate the set of candidate codewords. It uses the exact probability for each codeword as a new likelihood metric and a method to generate the appropriate set of codewords similar to Kaneko, et al., and Tanaka-Kakigahara algorithms. The performance of the proposed algorithm is the same as that of MLD as it is proved theoretically and verified by simulation results. The comparison with these similar algorithms shows that the new one always requires less average decoding complexity than those of the other algorithms. Finally, we compare the algorithms for terrestrial and satellite channels.     

Real-Domain Decoder for Full-Rate Full-Diversity STBC with Multidimensional Constellations

In this letter, we present a new maximum likelihood (ML) decoding algorithm for space time block codes (STBCs) that employ multidimensional constellations. We start with a lattice representation for STBCs which transforms complex channel models into real matrix equations. Based on the lattice representation, we propose a new decoding algorithm for quasiorthogonal STBCs (QO-STBC) which allows simpleML decoding with performance identical to the conventional ML decoder. Multidimensional rotated constellations are constructed for the QO-STBCs to achieve full diversity. As a consequence, for quasi-orthogonal designs with an arbitrary number of transmit antennas N (N ? 4), the proposed decoding scheme achieves full rate and full diversity while reducing the decoding complexity from ∂(M_c^N/2) to ∂(M_c^N/4) in a M_c-QAM constellation.     

完美空时分组码及其高性能解码算法

根据完美空时分组码（STBC）的结构特点提出了等效的垂直-贝尔实验室空时（V-BLAST）模型，在对该模型进行最小均方误差-判决反馈均衡（MMS-DFE）预处理之后，提出一种有边界约束的Fano解码器。该解码器可达到几乎最大似然（ML）性能，在很大的信噪比区域范围内其复杂度比目前典型的解码器低，而且该解码器可用于发射天线数大于接收天线数的系统。直接在复数域计算和处理，该解码器适用于任何星座形式。该解码器可用于任何能等效成V-BLAST模型的空时系统。仿真结果表明了该解码器的有效性。     

Multilevel block codes for Rayleigh-fading channels

New multilevel block codes for Rayleigh-fading channels are presented. At high signal-to-noise ratios (SNRs), the proposed block codes can achieve better bit error performance over TCM codes, optimum for fading channels, with comparable decoder complexity and bandwidth efficiency. The code construction is based on variant length binary component block codes. As component codes for the 8-PSK multilevel block construction, the authors propose two modified forms of Reed-Muller codes giving a good trade-off between the decoder complexity and the effective code rates. Code design criteria are derived from the error performance analysis. Multistage decoding shows very slight degradation of bit error performance relative to the maximum likelihood algorithm     

Universal decoding for memoryless Gaussian channels with adeterministic interference

A universal decoding procedure is proposed for memoryless Gaussian channels with deterministic interfering signals from a certain class. The proposed decoder is universal in the sense that it is independent of the channel parameters and the unknown interfering signal, and, at the same time, attains the same random coding error exponent as the optimal maximum likelihood (ML) decoder, which utilizes full knowledge of the channel parameters and the interfering signal. The proposed decoding rule can be regarded as a continuous-alphabet version of the universal maximum mutual information decoder     

FPGA implementation of low complexity LDPC iterative decoder

Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.     

基于MIMO系统的球形译码算法的改进

在最大似然检测中,球形译码算法是一种有效的快速算法。提出一种基于MIMO系统的新的快速球形译码算法,它的复杂度比传统的算法要小的多。在提出的方法中,初始半径的选择并不重要。这种改进算法的译码性能和复杂度由两个参数来控制。因此,该方法存在着译码性能和复杂度的均衡。通过计算机仿真,可以看到,提出改进算法的译码性能得到了较大的提高。     

Combined simplified maximum likelihood and sphere decoding algorithm for MIMO system

In this article, a new system model for sphere decoding （SD） algorithm is introduced. For the 2 × 2 multipleinput multiple-out （MIMO） system, a simplified maximum likelihood （SML） decoding algorithm is proposed based on the new model. The SML algorithm achieves optimal maximum likelihood （ML） performance, and drastically reduces the complexity as compared to the conventional SD algorithm. The improved algorithm is presented by combining the sphere decoding algorithm based on Schnorr-Euchner strategy （SE-SD） with the SML algorithm when the number of transmit antennas exceeds 2. Compared to conventional SD, the proposed algorithm has low complexity especially at low signal to noise ratio （SNR）. It is shown by simulation that the proposed algorithm has performance very close to conventional SD.