Research of fast decoding for longer constraint length convolutional codes

To overcome the disadvantage of Viterbi decoding algorithm, in which its complexity exponentially increases with the increasing constraint length of convolutional codes, and the decoding delay was too large to fit the decoding of longer constraint length convolutional codes, a fast decoding of convo...

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Main Authors: HUANG Xiao-ling, YANG Hua-long
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2010-01-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/74649328/
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author HUANG Xiao-ling
YANG Hua-long
author_facet HUANG Xiao-ling
YANG Hua-long
author_sort HUANG Xiao-ling
collection DOAJ
description To overcome the disadvantage of Viterbi decoding algorithm, in which its complexity exponentially increases with the increasing constraint length of convolutional codes, and the decoding delay was too large to fit the decoding of longer constraint length convolutional codes, a fast decoding of convolutional codes for longer constraint length, based on improved particle swarm optimization algorithm, was proposed. The proposed method reduces the searching area in the grid of decoding and shortens the decoding delay by setting the population size M to determine the number of decoding path, therefore was more suitable for longer constraint length convolutional codes. Another method of decoding convolu- tional codes based on self-adapting of decoding width was also proposed. Simulation results show that the proposed both methods have advantages in reducing the computational complexity and the decoding time.
format Article
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institution DOAJ
issn 1000-436X
language zho
publishDate 2010-01-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-ecc025f2eaa54b749d35b3b7068f559d2025-08-20T02:53:41ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2010-01-0131576474649328Research of fast decoding for longer constraint length convolutional codesHUANG Xiao-lingYANG Hua-longTo overcome the disadvantage of Viterbi decoding algorithm, in which its complexity exponentially increases with the increasing constraint length of convolutional codes, and the decoding delay was too large to fit the decoding of longer constraint length convolutional codes, a fast decoding of convolutional codes for longer constraint length, based on improved particle swarm optimization algorithm, was proposed. The proposed method reduces the searching area in the grid of decoding and shortens the decoding delay by setting the population size M to determine the number of decoding path, therefore was more suitable for longer constraint length convolutional codes. Another method of decoding convolu- tional codes based on self-adapting of decoding width was also proposed. Simulation results show that the proposed both methods have advantages in reducing the computational complexity and the decoding time.http://www.joconline.com.cn/zh/article/74649328/convolutional codesdecoding algorithmparticle swarm optimizationdecoding performance
spellingShingle HUANG Xiao-ling
YANG Hua-long
Research of fast decoding for longer constraint length convolutional codes
Tongxin xuebao
convolutional codes
decoding algorithm
particle swarm optimization
decoding performance
title Research of fast decoding for longer constraint length convolutional codes
title_full Research of fast decoding for longer constraint length convolutional codes
title_fullStr Research of fast decoding for longer constraint length convolutional codes
title_full_unstemmed Research of fast decoding for longer constraint length convolutional codes
title_short Research of fast decoding for longer constraint length convolutional codes
title_sort research of fast decoding for longer constraint length convolutional codes
topic convolutional codes
decoding algorithm
particle swarm optimization
decoding performance
url http://www.joconline.com.cn/zh/article/74649328/
work_keys_str_mv AT huangxiaoling researchoffastdecodingforlongerconstraintlengthconvolutionalcodes
AT yanghualong researchoffastdecodingforlongerconstraintlengthconvolutionalcodes