Research Article
A Minimum Distance guided Genetic Algorithm for Multi-User Detection in a Multi-Carrier CDMA Wireless Broadband System
@INPROCEEDINGS{10.1109/BROADNETS.2008.4769133, author={Qiang Ni and Jehanzeb Jehanzeb and Yang Zhang and Sheng-Uei Guan}, title={A Minimum Distance guided Genetic Algorithm for Multi-User Detection in a Multi-Carrier CDMA Wireless Broadband System}, proceedings={5th International ICST Conference on Broadband Communications, Networks, and Systems}, proceedings_a={BROADNETS}, year={2009}, month={1}, keywords={Genetic Algorithm MC-CDMA Multi-User Detection Multiple Access Interference}, doi={10.1109/BROADNETS.2008.4769133} }- Qiang Ni
Jehanzeb Jehanzeb
Yang Zhang
Sheng-Uei Guan
Year: 2009
A Minimum Distance guided Genetic Algorithm for Multi-User Detection in a Multi-Carrier CDMA Wireless Broadband System
BROADNETS
IEEE
DOI: 10.1109/BROADNETS.2008.4769133
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.
