Research On Multiuser Detection In CDMA Communication System

Multi-user detection (MUD) applies the user's PN sequence, delay, amplitude and phase information to make combined detection in order to control multiple access interference(MAI) , make full use of uplink frequency spectrum, promote system performance and capacity, which is one of the key technology for CDMA system. In this paper, During the project of airliner mobile communication technology study and absorbing the useful achievements, the writer applied subspace method to study on Multi-user detection algorithm, subspace tracking algorithm and spatial signature extraction, studied the suitable and feasible method to enhance the performance of MUD. Based on the study, the author proposed many linear blind adaptive MUD algorithm in order to improve the system performance. The major work and contribution are as following.Proposed the space- time blind adaptive MMSE multi-users detection algorithm on the base of subspace tracking. This algorithm makes use of array antenna technology to construct space-time signal model with spatial signature. On the least mean square error criterion, used subspace eigenvector, eigenvalue diagonal matrix and space-time manifold matrix to construct weight vector form of multi-user detection and avoid that MUD cann't effectively restrain co-channel interference in the time domain detection. Construct blind estimation algorithm of space-time signal channel parameters that there are space-time feature information in multi-users detection weight vector in order to improve the capacity of restraining MAI.Proposed one new linear MMSE blind adaptive multi-users detection algorithm. On the base of linear blind adaptive multi-users detection algorithm based on signal subspace, projected the receiving signal to signal subspace and solve inverse of autocorrelation matrix , and deduced detection algorithm without subspace eigenvalue matrix parameters and eliminated the error introduced by estimating eigenvalue matrix. Bit-error-ratio of the algorithms proposed is much lower than that of others subspace tracking algorithms.Proposed the linear MMSE blind adaptive multi-users detection algorithm based on the interference subspace. By performing the eigendecomposition of autocorrelation matrix of interference signal, author obtained eigenvector and eigenvalue matrix, and used interference subspace eigenvector, eigenvalue diagonal matrix to construct weight vector form of multi-user detection on the least mean square error criterion, and applied FAPI to estimate the interference subspace eigenvector. Simulation results show that , the Signal to interference ratio of the algorithms proposed is much better than that of others interference subspace tracking algorithms.In PASTd algorithm, when estimating subspace character vector, the vector is not strictly Orthogonal. For this question, the author proposes the linear MMSE blind adaptive multi-user detection algorithm on the base of NewPASTd. On the base of PASTd algorithm, in the process of iteration, make unit-norm orthogonalization to the eigenvector in order to make the estimated eigenvector orthogonal, and obtain an improved subspace tracking algorithm(NewPASd). Convergent rate of the algorithms proposed is much better than that of others subspace tracking algorithms. .After studying on the multi-user detection algorithm, author made simulation of several kinds of multi-user detection algorithm based on MATLAB. And the simulation result is almost the same with the theoretical analysis, which proves the feasibility and availability of the proposed multi-user detection algrithms.