An Approach To Blind Channel Identification By Estimating The Probability Density Function of Received Data

"A new blind channel estimation approach is presented in this paper, based on the well known probability density function estimation by Kullback-Leibler’s distance minimization. Thanks to a probability approximation, the resulting structure is surprisingly simple. Unfortunately, a complete analytic study of such a structure is quite difficult because of its nonlinear and recursive nature. Some approximated analytic expressions are presented along with some typical simulation results."