Multiuser Detection Using the Clonal Selection Algorithm and Hopfield Neural Network

摘要：

In this paper, we present multi-user detection technique based on a novel clonal selection algorithm (CSA) and Hopfield neural network ,for code-division multiple-access communications system. Using this approach, the Hopfield neural network is embedded into the CSA as an “immune operator to improve further the affinity of the antibodies at each generation. Such a hybridization of the CSA with the Hopfield neural network reduces its computational complexity by providing faster convergence. In addition, the embedded Hopfield neural network improves the performance of the CSA. Simulation results are provided to show that the proposed approach of multiuser detection has significant performance improvements over the conventional detector and some detectors based on the previous algorithms in bit-error-rate, multiple access interference and near-far resistance.

作者: Ma Jie Gao Hong-yuan Diao Ming

作者单位: School of Information and Communications Engineering, Harbin Engineering University,No.145.Nantong Street, Nangang, Dist, Harbin, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 739-743

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）