Evaluation of adaptive blind SIMO identification in terms of a normalized filter-projection misalignment
Evaluation of adaptive blind SIMO identification in terms of a normalized filter-projection misalignment
复制标题
根据归一化滤波器投影失准评估自适应盲 SIMO 识别
DOI：
10.1109/icassp.2011.5947264
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Gerald Enzner
中科院分区：
文献类型：
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作者：
D. Schmid;Gerald Enzner
单输入多输出(SIMO)系统的盲辨识在信道间存在接近公共且精确的公共零点时受到影响，特别是在与观测噪声相结合的情况下。一般来说，我们注意到识别的模糊性，如果没有关于信道系数的进一步的先验信息，就不能解决这一问题。为了能够在这种情况下对盲SIMO辨识进行充分的评估，我们提出了归一化滤波-投影错位(NFPM)，它表示真实通道和估计通道之间的多通道平方误差距离，同时吸收了由于可能缺乏可辨识性而导致的常见滤波误差。实验证明，在存在丢失信道分集和噪声的情况下，盲多信道最小均方(MCLMS)算法的稳态性能与有监督最小均方(LMS)系统辨识的结果是一致的。
The blind identification of single-input multiple-output (SIMO) systems suffers in the presence of near-common and exact common zeros between the channels, particularly in conjunction with observation noise. In general, we notice an ambiguity of the identification which cannot be resolved without further a priori information on the channel coefficients. In order to enable an adequate evaluation of blind SIMO identification in such cases, we develop the normalized filter-projection misalignment (NFPM), which represents a multichannel squared-error distance between true and estimated channels, while absorbing a common filter error due to a possible lack of identifiability. Using the NFPM measure, we demonstrate experimentally that the steady-state performance of the blind multichannel least mean-square (MCLMS) algorithm in the presence of missing channel diversity and noise is in line with the results obtained from supervised least mean-square (LMS) system identification.