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基于子空间方法的最小均方误差半盲多用户检测的计算核心是对信号子空间的特征值与特征向量的同时跟踪.仅跟踪计算信号子空间特征向量的子空间跟踪算法不能直接应用于这种检测方法.利用数据压缩技术,提出一种只需跟踪计算信号子空间正交规范基的自适应数据压缩半盲多用户检测.将著名的正交投影逼近子空间跟踪(OPAST)算法应用于这种数据压缩半盲多用户检测,发现OPAST算法具有自然的数据压缩结构,在几乎不增加运算量的情况下即可实现数据压缩半盲多用户检测.仿真实验表明:基于OPAST算法的数据压缩半盲多用户检测具有良好的检测性能.
The kernel of MSLS based on subspace method is to track the eigenvalues and eigenvectors of the signal subspace at the same time.The subspace tracking algorithm that tracks only the eigenvector of the signal subspace can not be applied directly to this This paper proposes an adaptive data compression semi-blind multi-user detection which only needs to track the orthonormal basis of signal subspace using data compression technique. The famous Orthogonal Projection Approximation Subspace Tracking (OPAST) algorithm is applied to This data compression semi-blind multi-user detection, found OPAST algorithm has a natural data compression structure, with little increase in the amount of computation to achieve data compression semi-blind multi-user detection.Simulation experiments show that: based on OPAST algorithm data compression Semi-blind multi-user detection has good detection performance.