Symbol detection in MIMO systems using SA-BFO optimization algorithm

Abstract: Multi-Input Multi-output based communication system architecture promises increased capacity and high data rates. Self-adaptive Bacterial Foraging Optimization (SA-BFO), inspired by foraging behaviour of bacteria, is one of the recent technologies in solving optimization problems. In this paper SA-BFO based algorithm for symbol detection in multi- input multi-output system is presented. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, simulation results show that the SA-BFO optimized MIMO detection algorithm results in near optimal Bit Error Rate (BER) performance , with significantly reduced complexity.

Keywords: MIMO (Multi-Input Multi-Output system), BER (Bit Error Rate) , SA-BFO (Self-Adaptive Bacterial Foraging Optimization algorithm), ML (Maximum Likelihood)