On the decoding of convolutional codes using genetic algorithms

Author

Berbia, Hassan ; Belkasmi, Mostafa ; Elbouanani, Fayssal ; Ayoub, Fouad

Author_Institution

ENSIAS, Rabat

fYear

2008

fDate

13-15 May 2008

Firstpage

667

Lastpage

671

Abstract

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.

Keywords

computational complexity; convolutional codes; data communication; decoding; digital communication; genetic algorithms; artificial intelligence; computing complexity; convolutional codes; data communication; decoding; digital communication; genetic algorithm based decoder; wireless communication; Artificial intelligence; Block codes; Computational modeling; Convolutional codes; Digital communication; Genetic algorithms; Genetic engineering; Iterative decoding; Turbo codes; Viterbi algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Engineering, 2008. ICCCE 2008. International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-1691-2

Electronic_ISBN

978-1-4244-1692-9

Type

conf

DOI

10.1109/ICCCE.2008.4580688

Filename

4580688