Global convergence of a blind multichannel identification algorithm

Authors:
Miloje Radenkovic;Tamal Bose
Affiliations:
Department of Electrical Engineering, University of Colorado at Denver, Denver, CO;Department of Electrical and Computer Engineering, Utah State University, 4120 Old Main Hill, Logan, UT
Venue:
Signal Processing
Year:
2004

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Abstract

In this paper, we propose an adaptive algorithm for blind identification of single-input multiple-output (SIMO) systems. The algorithm consists of p-1 parallel recursive estimators, where p is the number of system outputs. We analyze the normalized least-mean square (NLMS) estimator, and the weighted recursive least-squares (WRLS) algorithm. It is proved that parameter estimates converge toward a scalar multiple of the true parameters with probability one. The value of the scaling factor is calculated. Numerically simple p-1 parallel NLMS recursions are potential candidate for real-time blind identification applications.