Research On Blind Multi-user Detection Based On Improved ICA Algorithm

Code Division Multiple Access (CDMA) system is a developed spread spectrum wireless communication system, where multi-access interference (MAI) and Near-far effect exist. However, as the number of users or the signal power increases, MAI phenomenon is very serious which greatly limits the CDMA system performance. As one of the key technologies of the third generation mobile communication, multi-user detection (MUD) utilizes the internal structure information of user signature to reduce the multi-access interference, increase system capacity and solve the Near-far problem. The blind multi-user detection schemes do not require training sequences and the interference user’s information. It only needs the prior knowledge of the signature waveform and the timing of the desired user. It has good prospects for development with low complexity, less system requirements etc.This thesis takes blind multi-user detection based on independent component analysis (ICA) as research object. It summarizes the previous work, and proposes some new improved algorithms. The main works are as follows:Firstly, the basic concept and principle on the MUD are introduced and some mostly important MUD methods are summarized. Then the basic theory of the spread spectrum communication and ICA’s application in the field of MUD are introduced.Secondly, comparing the DS-CDMA and ICA signal models, ICA can be applied to blind MUD of DS-CDMA system. The ICA algorithm based on Chaos-Particle Swarm Optimization (CPSO-ICA) is proposed for multi-user detection. Comparing with the traditional ICA algorithm, the CPSO-ICA algorithm has better detection performance.Thirdly, this thesis introduces a kind of KICA algorithm, which is used to solve the current popularity nonlinear mixed problem, and brings in a new combination of kernel function. Then combined with CPSO-ICA algorithm, a CPSO-KICA blind MUD algorithm is proposed. Comparing with the traditional KICA algorithm, the simulation results show that the CPSO-KICA MUD algorithm has a short run time and good separation performance.Finally, the summary and the prospect on this research are given.