An Application of GA for Symbol Detection in MIMO Communication Systems

Abstract

Multi-input multi-output (MIMO) based communication system architecture promises increased capacity and high data rates. Increase in the number of transmit antennas and using higher order complex modulation schemes achieves even higher performance but with exponentially increasing complexity at the receiver end. This paper explores the application of genetic algorithm (GA) for reducing complexity in solving this NP hard problem. This approach is particularly attractive as GA is well suited for physically realizable, 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, simulation results show that the GA optimized MIMO detection algorithm results in near optimal bit error rate (BER) performance, with significantly reduced complexity. Results also suggest that the GA based MIMO detection out-performs the Vertical Bell labs Layered Space Time (V-BLAST) detector in BER performance without severely increasing the systems complexity.