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Comparative Analysis of GA-MMSE and PSO-MMSE Based MUD Technique Aided SDMA/OFDM System

Medha Vijayvargiya, Manish Kumar Gurjar

Smart antenna primarily uses the SDMA-OFDM based architecture of communication. Due to robustness and protection against interference provide by OFDM (Orthogonal Frequency division multiplexing). Although High data rate transmission is effectively achieved by using OFDM but detection techniques especially in over-loaded scenario poses many challenging issues. There are many optimization techniques presents for optimal multiuser detection process in SDMA-OFDM system, though each method is suffered from limitations. In these paper two popular evolutionary algorithms such as particle swarm optimization (PSO) hybrid with MMSE technique and genetic algorithm (GA) based SDMA-OFDM multi user detection (MUD) is hybrid with the MMSE technique. These optimization multiuser detection (MUD) techniques are simulated using three different modulation techniques these are PSK, QAM and its performance is compared against four existing MUDs such as MMSE(Minimum mean square) GA(Genetic Algorithm),PSO and ZF(Zero forcing) varying different parameters. Concatenated PSO-MMSE and GA-MMSE, the two methods are better in terms of simulation and reduces complexity. These techniques are proved to provide a very high performance when comparing with the existing detectors especially in a rank-deficient scenario in which numbers of users are very high as compare to transmitting antenna. From the experimental results it is crystal clear that GA-MMSE and PSO-MMSE improve the results by 29.8% than existing multiuser detection technique and BER reached to a level of 0.01.