Abstract
Effective channel order determination is an important problem in convolutive blind channel identification. The classical techniques are based on information theoretic criteria, which show a great potentiality to estimate the effective channel order. However, these methods are just effective for the overdetermined case, i.e., the number of sensors is larger than the number of source signals. When the number of sensors is less than or equal to the number of source signals, i.e., in the underdetermined or determined case, it is difficult to detect the effective channel order. In this paper, an improved algorithm is proposed to estimate the effective channel order by integrating numerical analysis arguments and higher-order cumulant tensor. In the proposed algorithm, we exploit the information contained in the higher-order data statistics and rearrange the tensor as a matrix using the unfolding operation, then utilize the eigenvalues of the matrix and combine numerical analysis arguments to detect the effective channel order. Finally, a series of experiment results demonstrate the effectiveness and superiority of the proposed algorithm.
Highlights
It is well known that a key issue is the determination of effective channel order in convolutive blind channel identification [1,2,3]
The information theoretic criteria have become the classical techniques [9,10], such as Bayesian information criterion (BIC) [11], generalized information criterion [12], the model selection introduced by Akaike information criterion (AIC) [13], by Schwartz and Rissanen minimum description length (MDL) [14,15], a method with the random matrix theory (RMT) algorithm [16], the automatic order selection [17], N-way probabilistic clustering [18,19]
We provided an improved algorithm by integrating the numerical analysis arguments and higher-order cumulant
Summary
It is well known that a key issue is the determination of effective channel order in convolutive blind channel identification [1,2,3]. A common assumption in some papers [4,5] is that the effective channel order is known. In practice, it is unknown and has an important effect on the channel identification. The effective channel order determination is a challenging problem to be solved in the blind channel identification. An effective method has been proposed based on numerical analysis arguments [20,21], which detects the effective channel order using a rank detection method to the single-input/multiple-output (SIMO) case.
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