基于FSYAST子空间算法的盲自适应多用户检测

Blind Adaptive Multiuser Detection Based on FSYAST Subspace Algorithm

  • 摘要: 为解决传统算法因引入特征值估计误差而导致检测性能下降的问题,在分析基于信号子空间跟踪的最小均方误差(MMSE)多用户检测器(MUD)的基础上,提出了一种改进的信号子空间盲线性MMSE多用户检测器,并应用FSYAST子空间跟踪算法进行信号子空间跟踪. 仿真结果表明,提出的盲自适应多用户检测器性能接近于奇异值分解(SVD)子空间多用户检测器性能.

     

    Abstract: The minimum mean square error (MMSE) multiuser detectors based on signal-subspace are deeply investigated. Fast and stable yet another subspace tracker(FSYAST)and an improved MMSE multiuser detector is designed to solve the problems of detecting performance degradation caused by eigenvalue estimation errors. The simulation results showed that, the performance of the proposed MMSE detector approaches that of the singular-value decomposition-based subspace multiuser detectors.

     

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