Abstract
While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, we show that binary Ant Colony Optimization (ACO) based Multi-Input Multi-Output (MIMO) detection algorithm gives near-optimal Bit Error Rate (BER) performance with reduced computational complexity. The simulation results suggest that the reported unconventional detector gives an acceptable performance complexity trade-off in comparison with conventional ML and non-linear Vertical Bell labs Layered Space Time (VBLAST) detectors. The proposed technique results in 7-dB enhanced BER performance with acceptable increase in computational complexity in comparison with VBLAST. The reported algorithm reduces the computer time requirement by as much as 94% over exhaustive search method with a reasonable BER performance.KeywordsSpatial Multiplexing SystemBinary Ant SystemSymbol detectionMulti-Input Multi-Output–Orthogonal Frequency Division Multi-plexing (MIMO-OFDM)
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