About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
IEEE TSP
Paper
Analysis of a nonparametric blind equalizer for discrete-valued signals
Abstract
An investigation is carried out to identify the variables that may affect the numerical properties of an inverse filtering method of blind equalization for linear channels with discrete input. The analysis is under a nonparametric framework in which all coefficients of the inverse filter (equalizer) can be freely chosen. It reveals, in particular, that the filter length plays two contradictory roles - increasing the length always helps improve the accuracy of inverse filtering, but when the filter is too long, the numerical properties of the method may deteriorate. Other influential variables include the constellation and (possibly time-varying) probability distribution of the input signals. The method is also shown to be highly efficient for nonparametric channel estimation, as was shown for estimating parametric channels. Simulations are carried out to verify the analytical findings concerning the numerical properties.