A Multiuser Detection for MC-CDMA System Based on Particle Swarm Optimization Algorithm with Hopfield Neural Network

In this paper, we propose a multiuser detection (MUD) for MC-CDMA system based on particle swarm optimization algorithm with Hopfield neural network (HNNPSO). In the updating of particles´ position, we choose some random particles as individuals composed of neurons in HNN to update the network, and employ PSO updating strategy to the others, which can provide faster rate of convergence and reduce the computational complexity of PSO algorithm. Simulation results show that the performance of the proposed MUD such as bit error rate, convergence, system capacity, and near-far resistance is better than that of MUD based on PSO and MUD based on HNN, nearly reaching the performance of optimal multiuser detection (OMD).