Home > Research > Publications & Outputs > A Minimum Distance guided Genetic Algorithm for...
View graph of relations

A Minimum Distance guided Genetic Algorithm for Multi-User Detection in a Multi-Carrier CDMA Wireless Broadband System

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Qiang Ni
  • Jehanzeb Jehanzeb
  • Yang Zhang
  • Sheng-Uei Guan
Close
Publication date2008
Host publicationBroadband Communications, Networks and Systems, 2008. BROADNETS 2008. 5th International Conference on
Place of PublicationNew York
PublisherIEEE
Pages500-505
Number of pages6
ISBN (print)978-1-4244-2391-0
<mark>Original language</mark>English
Event5th International Conference on Broadband Communications Networks and Systems - London
Duration: 8/09/200811/09/2008

Conference

Conference5th International Conference on Broadband Communications Networks and Systems
CityLondon
Period8/09/0811/09/08

Conference

Conference5th International Conference on Broadband Communications Networks and Systems
CityLondon
Period8/09/0811/09/08

Abstract

We propose a novel Minimum Distance guided Genetic Algorithm (MDGA) for Multi-User Detection (MUD) in a synchronous Multi-Carrier Code Division Multiple Access (MC-CDMA) broadband wireless system. In contrast to conventional GAs, our MDGA exploits adequately the output from a bank of Matched Filters as guidance. It starts with a balanced ratio of exploration and exploitation which is maintained throughout the process. A novel replacement strategy is proposed which increases dramatically the convergence rate as compared to the conventional GAs. This allows us to use the simplest form of genetic operators to gain significant reduction in computational complexity as well as near-optimum results. The simulation results demonstrate that our scheme achieves 99.54% and 50+% reduction in computational complexity as compared to the MUD schemes using exhaustive search and conventional GA respectively.