Fast maximum likelihood for blind identification of multiple FIR channels
Fast maximum likelihood for blind identification of multiple FIR channels
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DOI：
10.1109/78.489039
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发表时间：
1996-03
期刊：
影响因子：
--
通讯作者：
Y. Hua
中科院分区：
文献类型：
--
作者：
Y. Hua
本文提出了一种快速估计由任意未知输入驱动的多FIR信道脉冲响应的极大似然方法。所得到的方法包括两个迭代步骤，其中每一步最小化一个二次函数。两步最大似然（TSML）方法具有较高的信噪比效率，即在高信噪比下获得Cramer-Rao下界（CRB）。TSML方法利用了广义Sylvester矩阵的一种新的正交补矩阵。仿真结果表明，TSML方法明显优于相互关系（CR）方法和子空间（SS）方法，可以在较宽的信噪比范围内实现CRB。本文还研究了一个费雪信息矩阵来揭示m信道系统的可辨识性。在基于fi的可识别性和基于cr的可识别性之间建立了紧密的联系。
This paper develops a fast maximum likelihood method for estimating the impulse responses of multiple FIR channels driven by an arbitrary unknown input. The resulting method consists of two iterative steps, where each step minimizes a quadratic function. The two-step maximum likelihood (TSML) method is shown to be high-SNR efficient, i.e., attaining the Cramer-Rao lower bound (CRB) at high SNR. The TSML method exploits a novel orthogonal complement matrix of the generalized Sylvester matrix. Simulations show that the TSML, method significantly outperforms the cross-relation (CR) method and the subspace (SS) method and attains the CRB over a wide range of SNR. This paper also studies a Fisher information (FI) matrix to reveal the identifiability of the M-channel system. A strong connection between the FI-based identifiability and the CR-based identifiability is established.