SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Error Whitening Non-Parametric Maximum Likelihood Channel Estimator

Author(s)

Vimal Bhatia	University of Edinburgh, UK
Bernard Mulgrew	University of Edinburgh, UK

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Abstract

The presence of co-channel interference has been a major hindrance in improving the performance of present day communication systems. In this paper we discuss a iterative block based maximum-likelihood algorithm using kernel density estimates to improve channel estimation in presence of co-channel interference. As it is known that the interference is correlated, we first reduce this correlation by using a whitening filter. After whitening, we estimate this unknown whitened likelihood pdf by using kernel density estimator at the receiver. Thereby combining log-likelihood as cost function with whitening filter and kernel density estimate, a robust channel estimator for correlated noise environments is formed. The simulations for co-channel interference in presence of Gaussian noise, confirms that a better estimate can be obtained by using the proposed technique as compared to the traditional least squares algorithm, which is optimal in the Gaussian noise environments.