The Research On The Multi-User Detection Technology Based On Hopfield Neural Network

The third Generation mobile communication system includes highly effective channel encoding-decoding,software radio,smart antenna,multi-user detection and interference cancellation etc. In direct-sequence (DS-CDMA) system, multi-access interference is one of important factors that affect the systematic performance and capacity. Multi-user detection suppresses the interference at the receiver. The problem that it should solve is: How demodulate the bit information reliably of some specific user or all of the users from digital bits sequence that interference effectively by joint detection or subtract the MAI from the receiving signal according to the knowledge of sequence of all users basing on conventional detection of filter bank. Thus it can improve the performance of the system and increases capacity of the system.The main work of this paper is in several aspects as follows:1. The parameter and the performance of the Conventional Detector (CD),the Decorrelating Detector (DEC) and Minimum Mean Square Error detector (MMSE) have been analyzed in this paper.2. This paper has compared some conception of multi-user detector with some traditional multi-user detector algorithm in performance from the model of CDMA system.3. A multi-user detection algorithm based on the improved Stochastic Hopfield Neural Network (SHNN) has been proposed on this paper. Theory analysis of the algorithm and the performance analysis of MATLAB simulation are also given in this paper. Simulated results show that it can search the needed sequence rapidly and not easily gets into the minimum of energy. It can achieve better bit error rate and near-far resistance while SNR and interfere users' energy change. Analysis of the control parameters on performance of the system is verified by simulation...