Design of robust communication systems using genetic algorithms

Chien Min Ou, Wen Jyi Hwang*, Hung Chuan Yung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a novel genetic algorithm for jointly optimizing source and channel codes. The algorithm uses a channel-optimized vector quantizer for the source code, and a rate-punctured convolutional code for the channel code. The genetic algorithm enhances the robustness of the rate-distortion performance of the channel-optimized vector quantizer, and reduces the computational time for finding the best rate-punctured convolutional code. Numerical results show that the algorithm attains near optimal performance while having low computational complexity.

Original languageEnglish
Title of host publicationGenetic Programming - 9th European Conference, EuroGP 2006, Proceedings
Pages270-279
Number of pages10
DOIs
Publication statusPublished - 2006
Event9th European Conference on Genetic Programming, EuroGP 2006 - Budapest, Hungary
Duration: 2006 Apr 102006 Apr 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3905 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th European Conference on Genetic Programming, EuroGP 2006
Country/TerritoryHungary
CityBudapest
Period2006/04/102006/04/12

Keywords

  • Error Correct Coding
  • Genetic Algorithm
  • Vector Quantization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Design of robust communication systems using genetic algorithms'. Together they form a unique fingerprint.

Cite this