The Research On Linear Multiuser Detection Technology Based On Signal Subspace

In the code division multiple access (CDMA) communication system, the multiuser access interference (MAI) not only limits the system capacity, but also brings"far-near"effect which degrades the performance of system severely. The multiuser detection (MUD) can suppress the MAI effectively, and has become one of the critical techniques of the third generation mobile communication system.The MUD based on signal subspace can obtain the decorrelating detector and linear MMSE detector, which only requires the knowledge of signature waveform of desired user and timing of the system, and has the lower computational complexity in O ( NK )( N is the spreading gain and K is the number of users). For the classic subspace-based linear MMSE multiuser detector requires the estimation of eigenvalue matrix, there can be significant degradation in performance. Moreover, the approach to spatio-temporal structure did not sufficiently suppress the MAI but only improve the signal-to-noise ratio (SNR).Based on the deeply investigation on the subspace-based MMSE multiuser detection, the real time subspace-based MMSE multiuser detector is proposed, which improves the detection performance effectively. The received signal is projected into the signal subspace estimation achieved by subspace tracking algorithm, and then the weight vector is derived. The proposed algorithm offers stronger stability, faster convergence, lower computational complexity and better output signal-to-interference ratio (SIR) and bit-error ratio (BER).With the combination of the subspace tracking algorithm and the proposed algorithm, the spatio-temporal version of the proposed algorithm is proposed. By the subspace tracking approach, the desired signal steering vector can be resolved, which can be efficiently computed at a comparable cost with that of the classic method. Compared with the spatio-temporal version of the classic subspace-based MMSE multiuser detector, the proposed approach exploits the spatial characteristic of users, increases the ability against MAI of users, and extends the system capacity effectively.