Undermodeled equalization in noisy multi-user channels.
Phillip A. Regalia, Mamadou Mboup · NSIP · 1999
Blind equalization in noisy multi-user channels has met with increasing attention with the advent of multiaccess digital communication systems. We develop a unified formulation which combines the desired sources and the backgound noise into a common convolutional model. We then obtain a characterization of stationary points for a family of blind criteria in undermodeled cases, which incorporates the influence of differening source statistics and background noise correlation properties. We derive also a global step-size bound which ensures convergence of a gradient search procedure, and confirm that the superexponential algorithm results from an optimal choice of this step-size parameter.