Blind and semi-blind maximum likehood methods for FIR mutichannel identification

Ayadi, Jaouhar;de Carvalho, Elisabeth;Slock, Dirk T M
ICASSP 1998, 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, May 12-15, 1998, Seattle, USA

We investigate Maximum Likelihood (ML) methods for blind and semi-blind estimation of multiple FIR channels. Two blind De-terministic ML (DML) strategies are presented. In the first one,propose to modify the Iterative Quadratic ML (IQML) algo-rithm col-we in order to "denoise" it and hence obtain consistent chan-nel estimates. The second strategy, called Pseudo-Quadratic ML (PQML), is naturally asymptotically denoised. Links between these two approaches are established and their global convergence is proved. Furthermore, we propose semi-blind ML techniques com-bining with two different training sequenceestimation meth-ods in-PQML compare their performance. These semi-blind techniques, chan-and exploiting the presence of known symbols, outperform their blind version. They also allow channel estimation in situations where blind and training sequence methods fail separately. Simulations are presented to demonstrate the performance of all the proposed algorithms, and comparisons between them are discussedin a blind and/or semi-blind context.


DOI
Type:
Conférence
City:
Seattle
Date:
1998-05-12
Department:
Systèmes de Communication
Eurecom Ref:
83
Copyright:
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