Artificial Fish Swarm Algorithm-Assisted and Receive-Diversity Aided Multi-user Detection for MC-CDMA Systems

Artificial fish swarm algorithm (AFSA) assisted multi-user detection (MUD) is proposed for the receive-antenna-diversity-aided multi-carrier code-division multiple-access (MC-CDMA) systems in frequency selective fading channel. Due to the receive-diversity, the signals received at the different antennas are faded independently, resulting in an independent objective function for each antenna. To resolve the multi-objective dilemma when choosing one signal estimation for multiple receive antenna-branches, the individuals associated with the AFSA are selected based on the concept of Pareto optimality, which uses the information from the antennas independently. Simulation results showed that: with the same computation complexity, the strategy has much better bit error rate (BER) performance than the convention one. Comparisons with the conventional multiuser detector and the decorrelator verified the effectiveness of the proposed scheme.