Fast Decoding of Convolutional Codes Using Genetic Algorithm

CHEN Jun; SUN Shao-hui; WANG Xin-mei; CAO Zhi-gang

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Fast Decoding of Convolutional Codes Using Genetic Algorithm

更新时间：2025-07-16

- Fast Decoding of Convolutional Codes Using Genetic Algorithm
- Acta Electronica Sinica Vol. 28, Issue 9, Pages: 137-139(2000)
- 作者机构：
  
  1. 清华大学电子工程系,北京,100084
  2. 西安电子科技大学综合业务网国家重点实验室,西安,710071
  3. 清华大学电子工程系北京,100084
  4. 西安电子科技大学综合业务网国家重点实验室西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.22
- Published：2000
- 稿件说明：
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CHEN Jun, SUN Shao-hui, WANG Xin-mei, et al. Fast Decoding of Convolutional Codes Using Genetic Algorithm[J]. Acta Electronica Sinica, 2000, 28(9): 137-139.
DOI：

CHEN Jun, SUN Shao-hui, WANG Xin-mei, et al. Fast Decoding of Convolutional Codes Using Genetic Algorithm[J]. Acta Electronica Sinica, 2000, 28(9): 137-139. DOI：

摘要

本文提出基于遗传算法(GA)的卷积码快速译码

进行格图上的单向(U-GA)和双向(B-GA)搜索译码.它利用遗传算法的群体多样性好、搜索空间宽广

具有全局优化能力

提高译码质量.通过模拟计算

分析了单向和双向的译码算法和群体规模

M对误比特性能P

的影响.模拟结果表明:在相同译码复杂度下、P

=10

-6

时

与MA算法(编码约束度

=19)相比

该译码算法约有0.5dB性能增益;与VA算法(

=7)相比

B-GA大约有1dB增益.

Abstract

In this paper

fast decoding algorithms for convolutional codes

which are based on the genetic algorithm (GA)

are presented.They search from one side or both sides of the trellis respectively to implement unidirectional decoding (U-GA) or bi-directional decoding (B-GA).With good diversity

wide search region and global optimal ability of GA

the decoding performance can be improved.The effects of U- and B-GA and population size M on P

are analyzed.Simulation results show that

with the same decoding computation efforts and at P

=10

-6

B-GA achieves about 0.5 dB coding gains over M- algorithm (MA) for the coding constraint length K=19 code

and 1dB gain over Viterbi algorithm (VA) with the K=7 code.

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