Genetic Algorithm Optimization Tool for Multi-user Detection of SDMA-OFDM Systems

A tool is presented for achieving a near-optimum multi-user detector (MUD) based on the Genetic Algorithm (GA) techniques for Space Division Multiple Access (SDMA) Orthogonal Frequency Division Multiplexing (OFDM) communication systems. The tool involves methods for substantially reducing the GA search space to minimize the convergence time. GA parameters are investigated and the tool is investigated for the challenging overloaded scenario problem. Results reveal that the proposed tool provides a useful compromise means between performance and computational complexity. Simulation outcomes indicate that the tool surpasses the conventional low complexity methods, such as the minimum mean-square error (MMSE), and approaches the optimal performance of the Maximum Likelihood (ML) detector, while maintaining reduced complexity.