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.     

低莱斯因子衰落信道下的Turbo码性能研究

基于Turbo码编译码技术,在Rician衰落信道模型下,详细研究了Turbo码Log-MAP译码算法和SOVA译码算法在低Rician因子衰落信道下的性能,并结合调制技术对整个编译码系统进行Matlab仿真。仿真结果表明,在低Rician因子信道下,Log-MAP译码算法的性能优于SOVA译码算法。     

基于滑窗结构的软输出维特比算法的实现

文章在对软输出维特比算法(SOVA)进行推导的基础上，分析了软信息的提取过程。同时从硬件实现的角度考虑，提出了一种基于滑动窗1：3结构的SOVA算法实现方案，该算法大大降低了算法实现复杂度和译码延迟，同时通过调整滑窗参数，可以取得与非滑窗SOVA算法几乎相同的性能。     

深空通信中Turbo码的编译码技术

介绍了深空通信的发展现状和Turbo的国内外最新发展动态。分别对Turbo码的编码器部分，交织器部分和译码器部分的构成和性能进行了详细的分析，并着重论述了SOVA译码算法的原理及其译码过程。最后通过Matlab仿真图验证不同的交织长度以及各种译码算法所具有的译码性能和译码复杂度之间的关系。     

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。     

无线OFDM系统频率选择性衰落信道下的SOVA译码算法

本文对正交频分复用(OFDM)系统频率选择性衰落信道中,信道状态信息(channel state information 简称CSI)确知,以及CSI不能或不必精确估计时的SOVA译码算法进行了研究,给出了OFDM系统频率选择性信道BPSK调制时SOVA译码算法的数学描述.在此基础上,我们提出了两种SOVA译码算法:一种是基于盲信道估计的SOVA算法;另一种是不必训练和信道估计的差分SOVA算法,该算法可以在CSI完全未知的情况下进行可靠的SOVA译码.仿真结果说明该算法具有良好的性能.     

SOVA算法对Viterbi算法的修正

在Viterbi算法中引入软值进行修正之后的算法称作SOVA算法(Soft Output Viterbi Algorithm)。SOVA算法在Viterbi算法的基础上,路径量度引入了比特先验信息,对每位译码比特以后验概率似然比的形式提供软输出,因而可提供更高的译码性能。特别,SOVA算法可用于级联码的迭代译码,采用Tuobo原理使不同分量码之间交换软信息,从而可显著提高这类码的纠错能力。     

Turbo码译码的改进SOVA算法

Turbo编码自1993年提出以来，由于其出色的译码性能，在编码界得了广泛关注，逐渐被吸纳到一些标准化体系中，对于Turbo码的译码问题，目前已有许多种译码算法，在传统SOVA（软输出维特比算法）译码算法的基础上，给出了一种SOVA译码的改进算法，仿真结果表明该算法在译码性能等方面具有较强的优越性。     

MIMO低复杂度空时分组码译码算法研究

研究了空时分组码译码算法的运算简化问题,提出了一种基于最大似然检测的改进空时分组码低复杂度译码算法,并进行了译码性能仿真和运算复杂度对比。本丈提出的改进方法,能够在不影响系统译码性能的基础上,有效地降低空时分组码的译码复杂度,且译码复杂度受调制星座图大小的影响很小。     

Turbo码各种译码算法复杂度研究

在Turho码的两种经典译码算法:SOVA和MAP的基础上,介绍了两种改进的译算法:AL-1和AL-2。探讨了它们的计算复杂度。结果表明,在白高斯噪声信道下,AL-1和AL-2算法可大大减少计算复杂度。     

Bi-directional SOVA decoding for turbo-codes

In this letter, we present a bi directional SOVA-based decoding scheme for turbo-codes, which combines the soft-outputs provided by both forward and backward SOVA decodings. Importantly, we explain why this bi-directional decoding improves SOVA decoding. The simulation results show that bi-directional SOVA can achieve about the same performance as the Max-Log-MAP algorithm in turbo decoding     

New Soft Output Viterbi Algorithm for Mobile Communication System

Soft output Viterbi algorithm(SOVA) is a turbo decoding algorithm that is suitable for hardware implementation. But its performance is not so good as maximum a posterior probability(MAP) algorithm. So it is very important to improve its performance. The non-correlation between minimum and maximum likelihood paths in SOVA is analyzed. The metric difference of both likelihood paths is used as iterative soft information, which is not the same as the traditional SOVA. The performance of the proposed SOVA is demonstrated by the simulations. For 1024-bit frame size and 9 iterations with signal to noise ratio from 1dB to 4dB, the experimental results show that the new SOVA algorithm obtains about more 0.4dB and 0.2dB coding gains more than the traditional SOVA and Bi-SOVA algorithms at bit error rate(BER) of 1×10~ -4 , while the latency is only half of the Bi-direction SOVA decoding.     

List and soft symbol output Viterbi algorithms: extensions andcomparisons

The Viterbi algorithm (VA) is the maximum likelihood decoding algorithm for convolutionally encoded data. Improvements in the performance of a concatenated coding system that uses VA decoding (inner decoder) can be obtained when, in addition to the standard VA output, an indicator of the reliability of the VA decision is delivered to the outer stage of processing. Two different approaches of extending the VA are considered. In the first approach, the VA is extended with a soft output (SOVA) unit that calculates reliability values for each of the decoded output information symbols. In the second approach, coding gains are obtained by delivering a list of the L best estimates of the transmitted data sequence, namely the list Viterbi decoding algorithm (LVA). Our main interest is to evaluate the LVA and the SOVA in comparison with each other, determine suitable applications for both algorithms and to construct extended versions of the LVA and the SOVA with low complexity that perform the task of the other algorithm. We define a list output VA using the output symbol reliability information of the SOVA to generate a list of size L and that also has a lower complexity than the regular LVA for a long list size. We evaluate the list-SOVA in comparison to the LVA. Further, we introduce a low complexity soft symbol output viterbi algorithm that accepts the (short) list output of the LVA and calculates for each of the decoded information bits a reliability value. The complexity and the performance of the soft-LVA (LVA and soft decoding unit) is a function of the list size L. The performance of the soft-LVA and the SOVA are compared in a concatenated coding system. A new software implementation of the iterative serial version of the LVA is also included     

On the equivalence between SOVA and max-log-MAP decodings

It is shown that after a proper simple modification, the soft-output Viterbi algorithm (SOVA) proposed by Hagenauer and Hoeher (1989) becomes equivalent to the max-log-maximum a posteriori (MAP) decoding algorithm. Consequently, this modified SOVA allows to implement the max-log-MAP decoding algorithm by simply adjusting the conventional Viterbi algorithm. Hence, it provides an attractive solution to achieve low-complexity near-optimum soft-input soft-output decoding     

一种新的基-4SOVA译码算法

SOVA (Soft Output Viterbi Algorithm)类算法因其译码时延远低于MAP类算法已成为Turbo码的实用译码算法,为了进一步减小译码延迟,提高译码速度,该文在简单分析基-4Max-Log-MAP算法的基础上,提出了一种新的基-4SOVA算法,并进行了完整的数学推导.该算法的关键是提出了一种新...     

等价于MAP的SOVA译码方法

不同于MAP(Maximum A Posteriori)算法,SOVA(Soft-Output Viterbi Algorithm)算法的软输出不是真正意义上的后验概率,很少有文献给出SOVA算法的完整数学解释。该文给出了一种完整的SOVA的数学表达形式,并从SOVA的数学表达出发推导出了两种等价于MAP,具有SOVA形式的译码方法,一种是Li等人(1995)给出的适用于连续传输的最佳软输出算法(Optimal Soft output Algorithm, OSA);后一种是对OSA算法的改进,后者可以得到与前者等价的软输出,但是降低了运算复杂度。     

Complexity Reduction in SISO Decoding of Block Codes

SISO decoding for block codes can be carried out based on a trellis representation of the code. However, the complexity entailed by such decoding is most often prohibitive and thus prevents practical implementation. This paper examines a new decoding scheme based on the soft-output Viterbi algorithm (SOVA) applied to a sectionalized trellis for linear block codes. The computational complexities of the new SOVA decoder and of the conventional SOVA decoder, based on a bit-level trellis, are theoretically analyzed and derived for different linear block codes. These results are used to obtain optimum sectionalizations of a trellis for SOVA. For comparisons, the optimum sectionalizations for Maximum A Posteriori (MAP) and Maximum Logarithm MAP (Max-Log-MAP) algorithms, and their corresponding computational complexities are included. The results confirm that the new SOVA decoder is the most computationally efficient SISO decoder, in comparisons to MAP and Max-Log-MAP algorithms. The simulation results of the bit error rate (BER) performance, assuming binary phase -- shift keying (BPSK) and additive white Gaussian noise (AWGN) channel, demonstrate that the performance of the new decoding scheme is not degraded. The BER performance of iterative SOVA decoding of serially concatenated block codes shows no difference in the quality of the soft outputs of the new decoding scheme and of the conventional SOVA.