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机构地区:[1]西北工业大学电子信息学院,陕西西安710072
出 处:《西北工业大学学报》2008年第1期53-56,共4页Journal of Northwestern Polytechnical University
基 金:航空基础科学基金(2006ZC53023);陕西省自然科学基金(2007F23)资助
摘 要:为解决多用户检测系统复杂度与检测性能之间的矛盾,文中设计了一种改进的子空间盲多用户检测系统。该检测系统使用了一种计算复杂度较低且收敛性能较好的子空间算法——基于幂迭代的子空间算法,通过将该算法应用于修正的最小均方误差检测器(MMSE MUD)模型中得到一种改进的多用户检测系统,由于修正的MMSE MUD相对于经典的MMSE MUD减小了近似估计引入的误差,因此文中设计的检测系统可获得复杂性、收敛性能及稳态性能等多方面的益处。仿真实验验证了该检测系统的有效性。Aim. In the traditional blind multiuser detector (MUD), satisfactory convergence speed and stability require much computational complexity. We now present a blind MUD based on improved subspace tracking algorithm that we believe can reduce considerably computational complexity while keeping satisfactory convergence speed and stability unchanged. In the full paper, we explain the blind MUD in some detail) in this abstract, we just add some pertinent remarks to listing the two topics of explanation. The first topic is: the modified model of minimum mean square error(MMSE) MUD. In this topic, we point out that the modified model reduces the errors caused by subspace estimation and improves the detection performance of the blind MUD. The second topic is. the improved subspace tracking algorithm based on power iteration. In this topic, we present the iteration process of the algorithm to obtain the main signal subspace, as given in eqs. (11) through (19) in the full paper. The algorithm with power iteration has global convergence while reducing computational complexity considerably. Finally we simulate our algorithm in comparison with the OPAST algorithm. The simulation results, shown in Figs. 1 and 2 in the full paper, demonstrate preliminarily that our algorithm converges much faster and its stability is better than the OPAST algorithm and that its MMSE is much lower than that of OPAST algorithm, while keeping the computational complexity unchanged. The simulation results thus verify the effectiveness of the blind MUD.
关 键 词:盲多用户检测器 改进的子空间跟踪算法 幂迭代 最小均方误差
分 类 号:TN911[电子电信—通信与信息系统]
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