turbo码自由距离确定的改进子码约束算法

Suyue Gao, Qingchun Chen, Jiaxiang Li, Zheng Ma, P. Fan
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引用次数: 0

摘要

为了提高Turbo码自由距离确定的子码约束算法的计算效率,本文提出了两种有效的技术。首先,已知在一定输入约束条件下,确定递归系统卷积(RSC)码的最小输出汉明权值是Turbo码权值分配计算约束子码算法中的关键问题。利用改进的Viterbi算法求解该问题。本文引入了一种基于后向状态转移(BST)的算法来确定给定输入约束条件下RSC码的最小输出汉明权值。虽然也采用了基于状态转移的计算,但研究表明,通过充分利用给定RSC码的状态转移特征,可以将多步计算合并为一步计算,从而提高了确定RSC码最小输出汉明权值的计算效率。其次,提出在实现子码算法时采用后向计算过程代替前向计算过程。验证了所提出的反求方法可以加快Turbo码自由距离的确定速度。并以3GPP标准Turbo码为例,验证了改进方案的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the improved sub-code constrained algorithm for the determination of free distance for turbo codes
In this paper, two effective techniques are proposed to improve the computation efficiency of the sub-code constrained algorithm for the determination of free distance for Turbo codes. Firstly, it is known that, the determination of the minimum output Hamming weight of the recursive systematic convolutional (RSC) code under some input constraints is the crucial problem in the constrained sub-code algorithm towards the weight distribution calculation for Turbo codes. And the modified Viterbi algorithm was utilized to solve this problem. In this paper, the backward state transition based (BST) algorithm is introduced to determine the minimum output Hamming weight of the RSC codes for the given input constraints. Although the state transition-based calculation is utilized as well, it is shown that, by making full use of the state transition characteristics of the given RSC codes, multiple step calculations may be merged into one step calculation, thus improving the computation efficiency when determining the minimum output Hamming weight of the RSC code. Secondly, it is proposed to employ the backward computation procedure instead of the forward one when implementing the sub-code algorithm. And it is validated that, the proposed backward computation method could be utilized to speed up the determination of the free distance for Turbo codes. And the 3GPP standard Turbo code is used as an example to validate the applicability of the proposed improved schemes.
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