Paper Info
Title
Symbol detection in spatial multiplexing system using particle swarm optimization meta-heuristics
Abstract
Symbol detection in multi-input multi-output (MIMO) communication systems using different particle swarm optimization (PSO) algorithms is presented. This approach is particularly attractive as particle swarm intelligence is well suited for real-time applications, where low complexity and fast convergence is of absolute importance. While an optimal maximum likelihood (ML) detection using an exhaustive search method is prohibitively complex, PSO-assisted MIMO detection algorithms give near-optimal bit error rate (BER) performance with a significant reduction in ML complexity. The simulation results show that the proposed detectors give an acceptable BER performance and computational complexity trade-off in comparison with ML detection. These detection techniques show promising results for MIMO systems using high-order modulation schemes and more transmitting antennas where conventional ML detector becomes computationally non-practical to use. Hence, the proposed detectors are best suited for high-speed multi-antenna wireless communication systems. Copyright © 2008 John Wiley & Sons, Ltd.
Year
DOI
Venue
2008
10.1002/dac.v21:12
Int. J. Communication Systems
Keywords
Field
DocType
mimo,ofdm,particle swarm optimization,ml detection
Particle swarm optimization,Mathematical optimization,Brute-force search,Computer science,MIMO,Algorithm,Real-time computing,Spatial multiplexing,Orthogonal frequency-division multiplexing,Computational complexity theory,Bit error rate,Metaheuristic
Journal
Volume
Issue
ISSN
21
12
1074-5351
Citations 
PageRank 
References 
0
0.34
21
Authors
5
Name
Order
Citations
PageRank
Adnan Ahmed Khan1287.09
Sajid Bashir2305.70
Muhammad Naeem348874.69
Syed Ismail Shah48714.31
Xiaodong Li5156084.64