一种改进的基于卡尔曼滤波的盲多用户检测算法

Improved Blind Multiuser Detection Algorithm Based on Kalman Filtering

针对卡尔曼滤波盲多用户检测算法在多径信道存在波形失配的情况下性能迅速下降的问题,引入子空间概念对原状态空间模型进行了改进,进而得到了改进的盲多用户检测算法。该算法将检测器模型化为信号子空间的一个向量,采用卡尔曼滤波器自适应地获得系统参数。仿真实验表明,与原算法相比,该算法具有更低的计算复杂度和更快的收敛速度。当发生波形失配使信号受到严重削减时,该算法仍然表现出较好的性能。

Aimed at the problem in the Kalman multiuser detector with a rapid performance degradation in the presence of signature waveform mismatch in the multipath channel, an improved blind multiuser detection algorithm is presented based on Kalman filtering. The method introduces the subspaee technique to modify original state space model, thus the detector is modeled as a vector in the signal subspace. By using the Kalman filtering to derive its coefficients adaptively, an improved Kalman multiuser detector is formed. Simulation results demonstrate that the proposed scheme has the lower computational complexity and the fast convergence rate compared with that the orignal method. Furthermore, when the signature waveform mismatch causes serious cancellation of the desired user signal, the improved scheme has better performance.