Hybrid intelligence techniques for multiuser detection in DS-CDMA UWB systems

Direct-sequence code division multiple access ultra-wideband (DS-CDMA UWB) is proposed by Federal communication commission (FCC) as an alternate physical layer communication platform for Wireless sensor network (WSN). In this paper, the problem of multiple access interference (MAI) and inter-symbol interference (ISI) suppression in DS-CDMA UWB systems would be considered. This paper is dedicated to the application of intelligence computational techniques based on bionics to solve the difficult issue of multiuser detection (MUD) design capable of canceling the so-called MAI to reach low bit error rate with acceptable computation complexity. We apply the hybrid approach that employs a hopfield neural network (HNN) and particle swarm optimization (PSO) for the MUD problem in DS-CDMA UWB systems. The computer experiments show that the proposed HNN embedded PSO technique (HNNPSO) technique not only can find optimal or close-to-optimal solutions but also obtain both better and more robust results than the existing algorithm reported recently in this literature.