Asynchronous MC-CDMA multiuser detection employing hybrid immune clonal selection algorithm

In this paper, we present an multiuser detection (MUD) method employing hybrid immune clonal selection algorithm (ICSA) for an asynchronous multicarrier codedivision multiple-access (MC-CDMA) communications systems in frequency selective Rayleigh fading channels. We consider the MUD problem from a combinatorial optimization viewpoint and introduce the ICSA in heuristic search by imitating the evolutionary mechanism of antibodies. Moreover, Hopfield neural networks (HNNs) are embedded into the ICSA to improve further the affinity of the antibodies at each generation. In this way, computational complexity of the hybrid ICSA scheme called ICSAHNN can be reduced due to fast convergence of the HNN operator. Simulation results are also shown that the proposed scheme can achieve significant performance improvement in terms of bit-errorrate (BER) with an lower complexity.