基于子空间跟踪算法的盲多用户检测技术研究

Research of Blind Mulitiuser Detection Based on Subspace Tracking Algorithm

本文提出一种基于压缩投影逼近子空间跟踪(PASTd)算法与Kalman滤波算法相结合的盲自适应多用户检测算法。基于本算法,仅使用期望用户的特征波形和定时信息,多用户检测器可以盲获得。仿真实验表明,在多径非频率选择性衰落信道和用户数目变化的动态环境中,本文提出的盲多用户检测算法虽然在计算量上较LMS算法略为提高,但其收敛性能却优于后者,与RLS算法和Kalman滤波算法相比,本文提出的算法具有更低的计算复杂度和更优的收敛性能。

A blind adaptive multiuser detection algorithm based on a hybrid of Projection Approximation Subspace Tracking with deflation （PASTd） and Kalman filtering is proposed. It is shown that under this algorithm,multiuser detector can be obtained blindly using only the signature waveform and the timing of the desired user. The proposed blind muhiuser detection algorithm has a little higher computational quantity and excellent convergence performance than LMS algorithm, but it offers lower computational complexity and better convergence performance than RLS and Kalman filtering algorithm.