On the decoding of convolutional codes using Genetic Algorithms

被引：4
|
作者：
Berbia, Hassan
Belkasmi, Mostafa
Elbouanani, Fayssal
Ayoub, Fouad
机构：
来源：
2008 INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION ENGINEERING, VOLS 1-3 | 2008年
关键词：
D O I：
10.1109/ICCCE.2008.4580688
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we deal with decoding of convolutional codes using artificial intelligence techniques. A comparison of our decoder versus the Viterbi decoder in terms of performance and computing complexity is given. The simulation results show that the Genetic Algorithms based decoder (GAD) outperforms the Viterbi decoders. Furthermore the computing complexity of GAD is better for codes with large lengths. The good results obtained by GAD for systematic convolutional codes make it more attractive.
引用
收藏
页码：667 / 671
页数：5
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