Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - A Minimum Distance guided Genetic Algorithm for Multi-User Detection in a Multi-Carrier CDMA Wireless Broadband System
AU - Ni, Qiang
AU - Jehanzeb, Jehanzeb
AU - Zhang, Yang
AU - Guan, Sheng-Uei
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Genetic Algorithm
KW - MC-CDMA
KW - Multi-User Detection
KW - Multiple Access Interference
U2 - 10.1109/BROADNETS.2008.4769133
DO - 10.1109/BROADNETS.2008.4769133
M3 - Conference contribution/Paper
SN - 978-1-4244-2391-0
SP - 500
EP - 505
BT - Broadband Communications, Networks and Systems, 2008. BROADNETS 2008. 5th International Conference on
PB - IEEE
CY - New York
T2 - 5th International Conference on Broadband Communications Networks and Systems
Y2 - 8 September 2008 through 11 September 2008
ER -