A two-stage algorithm for MIMO blind deconvolution of nonstationary colored signals

A new two-stage algorithm is proposed for the deconvolution of multi-input multi-output (MIMO) systems with colored input signals. While many blind deconvolution algorithms in the literature utilize high order statistics of the output signal for white input signals, the additional information contained in colored input signals allows the design of second-order statistical algorithms. In fact, practical signal sources such as speech signals do have distinct, nonstationary, colored power spectral densities. We present a two-stage signal separation approach in which the first step utilizes a matrix pencil between output auto-correlation matrices at different delays, whereas the second stage adopts a subspace method to identify and deconvolve MIMO systems.

[1]  Adel Belouchrani,et al.  A new composite criterion for adaptive and iterative blind source separation , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[2]  Jitendra K. Tugnait,et al.  Blind equalization and channel estimation for multiple-input multiple-output communications systems , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[3]  Tapan K. Sarkar,et al.  On SVD for estimating generalized eigenvalues of singular matrix pencil in noise , 1991, IEEE Trans. Signal Process..

[4]  Ehud Weinstein,et al.  New criteria for blind deconvolution of nonminimum phase systems (channels) , 1990, IEEE Trans. Inf. Theory.

[5]  Dirk T. M. Slock,et al.  Blind fractionally-spaced equalization, perfect-reconstruction filter banks and multichannel linear prediction , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[6]  Philippe Loubaton,et al.  On subspace methods for blind identification of single-input multiple-output FIR systems , 1997, IEEE Trans. Signal Process..

[7]  Yingbo Hua,et al.  Techniques of Eigenvalues Estimation and Association, , 1997, Digit. Signal Process..

[8]  Sze Fong Yau,et al.  A cumulant-based super-exponential algorithm for blind deconvolution of multi-input multi-output systems , 1998, Signal Process..

[9]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[10]  Y. Li,et al.  Blind channel identification based on second order cyclostationary statistics , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  Lang Tong,et al.  Blind identification and equalization based on second-order statistics: a time domain approach , 1994, IEEE Trans. Inf. Theory.

[12]  Y. Sato,et al.  A Method of Self-Recovering Equalization for Multilevel Amplitude-Modulation Systems , 1975, IEEE Trans. Commun..

[13]  Ehud Weinstein,et al.  Criteria for multichannel signal separation , 1994, IEEE Trans. Signal Process..

[14]  Eric Moulines,et al.  Subspace methods for the blind identification of multichannel FIR filters , 1995, IEEE Trans. Signal Process..

[15]  Pierre Comon,et al.  Blind separation of sources, part II: Problems statement , 1991, Signal Process..

[16]  Zhi Ding,et al.  A matrix-pencil approach to blind separation of non-white sources in white noise , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).