Abstract
AbstractSymbol 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.
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