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

There is multiple access interference(MAI)in MC-CDMA which is a interference limited system.This paper presents a multiuser detection(MUD)for MC-CDMA system based on particle swarm optimization(PSO)algorithm with Hopfield neural network(HNN).In the updating of particles position,choosing some random particles as individuals composed of neurons in HNN to update the network,and employing 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,rate of convergence,system capacity,and near-far resistance is better than that of MUD based on PSO and MUD based on HNN,and nearly reaching the performance of optimal multiuser detection(OMD),when same parameters are used in these algorithms.