Robust subsystems for iterative multichannel blind system identification and equalization
Robust subsystems for iterative multichannel blind system identification and equalization
复制标题
用于迭代多通道盲系统识别和均衡的鲁棒子系统
DOI：
10.1109/pacrim.2009.5291250
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Gerald Enzner
中科院分区：
文献类型：
--
作者：
D. Schmid;Gerald Enzner
提出了一种多通道盲系统辨识的迭代方法。该概念包括两个用于信道识别和均衡的子系统，它们是专门为鲁棒相互作用量身定制的。当没有关于信道或输入信号的合适的先验信息可用时，这种鲁棒性是迭代系统收敛的自然前提。对于信道识别子系统，我们引入了一种监督的可变步长lms型自适应算法，该算法能够从估计的输入信号中识别信道。然后，我们证明了匹配的滤波器阵列可以作为均衡子系统来估计输入信号在识别通道的基础上。最后，我们证明了两个子系统的迭代耦合收敛于一个解，该解的质量可以通过我们对独立子系统的综合分析来预测。
This paper presents an iterative approach to multi-channel blind system identification. The concept includes two subsystems for channel identification and equalization which are specifically tailored for robust mutual interaction. This robustness is a natural prerequisite for the convergence of iterative systems when no suitable a priori information about the channels or the input signal is available. For the channel identification subsystem, we introduce a supervised, variable stepsize LMS-type adaptive algorithm which is able to identify the channels from an estimated input signal. We then show that matched filter arrays can be utilized as the equalization subsystem to estimate the input signal on the basis of the identified channels. Eventually, we demonstrate that the iterative coupling of both subsystems converges to a solution, the quality of which can be predicted from our comprehensive analysis of the independent subsystems.