Title :
On the decoding of convolutional codes using genetic algorithms
Author :
Berbia, Hassan ; Belkasmi, Mostafa ; Elbouanani, Fayssal ; Ayoub, Fouad
Author_Institution :
ENSIAS, Rabat
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;
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
DOI :
10.1109/ICCCE.2008.4580688
