基于子空间跟踪和卡尔曼滤波的半盲多用户检测

Semi-Blind Multiuser Detection Based on Subspace Tracking and Kalman Filter

本文研究多载波CDMA(MC-CDMA)上行链路半盲多用户检测技术,提出了一种基于子空间跟踪和卡尔曼滤波的半盲多用户检测算法。利用小区内所有用户的扩频码修改约束条件并采用修正的紧缩近似投影子空间跟踪(PASTd)算法和卡尔曼滤波算法求解优化问题,该算法利用已知的信息消除多址干扰,提高了系统的性能,同时避免了常规卡尔曼滤波算法的特征值分解问题,显著降低了计算复杂度。仿真实验验证了本文算法具有很好的检测性能和较强的抗多址干扰能力。

Semi-blind muhiuser detection is investigated for muhicarrier CDMA （MC-CDMA） uplink. A semi-blind multiuser detection algorithm based on subspace tracking and Kalman filter is proposed. This algorithm exploits the spreading sequences of all known users to modify constraint condition and solves the optimization problem by adopting the modified projecting approximation subspace tracking with deflation （PASTd） algorithm and Kalman filter. As a result ,the performance of the system is improved by making use of all the known information and the computational complexity is reduced to avoid the problem of eigen-decomposition in conventional Kalman filter. Simulation results demonstrate that the proposed method offers high detecting performance and has strong ability to eliminate multiple-access interference.