A Blind Adaptive SOR/JGS Iterative Kalman MUD Algorithm for Multiple Access Communication System

Abstract

Based on the fast stable convergence characteristics of successive over relaxation (SOR) iterative and Jacobi Gauss- Seidel (JGS) iterative, a blind adaptive SOR/JGS iterative Kalman multi-user detection (MUD) algorithm (SJK) is proposed for multiple access communication system as direct sequence spread spectrum code division multiple access (DS- CDMA) system with multi-path fading channel. The proposed combination of blind adaptive Kalman filtering theory, SOR and JGS iterative method can adaptively control the selection of relaxation parameters and damping parameter, and then effectively deal the problem as time-varying noise statistics estimation. Compared with traditional standard Kalman filter (SKF), fading Kalman filter (FKF) and robust adaptive Kalman filter (RAKF) algorithm, the proposed algorithm can effectively estimate unknown noise statistics characteristics on-line while conducting state filtering, totally track the time-varying channel, minimize the detection error diffusion, and thus effectively reduce multiple access interference (MAI). Simulation results show that the SJK algorithm is of better detection accuracy, convergence ability, dynamic tracking capability, and lower bit error rate (BER) performance.  Index Terms communication system is asynchronous or synchronous. When the distance between interference user and base station is closer than expected user, the received power of interference user would be much larger than expected user, then the correlation between spreading sequence and interference user would surely be much larger than that between spreading sequence and expected user. This would always cause a significant increase of MAI component in the traditional Multi-User Detection (MUD) receiver, and it may easily cause that the expected user signal is submerged by interference user signal. Namely, the Bit Error Rate (BER) of MUD receiver is very sensitive to the difference between expected user and interference user. Based on the above situation, the traditional MUD algorithm for DS-CDMA system such as Matched Filter (MF) and decorrelation detection receiver cannot effectively eliminate the impact of MAI and FNP. This makes SKF, Fading Kalman Filter (FKF) and Robust Adaptive Kalman Filter (RAKF) the focus of research.