The analytical method of Genetic Algorithm -Aided Iterative Joint Channel Estimation and Multi-User Detection

This is a recent research on Space-Division-Multiple-Access-Orthogonal frequency Division Multiplexing (SDMA-OFDM) for channel estimation based on iterative joint channel estimation and a new Genetic Algorithm (GA). Assisted iterative joint channel estimation and Multi-User Detection (MUD) is the most recent approach for MTMO SDMA-OFDM systems and GA-aided MUD techniques for providing the best capacity of ¿soft¿ outputs of the Generic Algorithm. These are the key technology in wireless communication. The main focus of this research is based on the Uniform Cross-over technique used for mutating the symbol chromosomes to obtain an initial Frequency Domain-CHannel Transfer Function (FD-CHTF). Based on the analysis of the Genetic Algorithm -Aided Iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) on individual-based or population-based on soft output single application an increase in number of users is obtained couple with resolve in the Multi-User Interference through perturbation technique in the SDMA-OFDM system. Finally, a range of simulation results are provided to demonstrate the improvement of the performance.