Wavelet-based separating kernels for sequence estimation with unknown rapidly time-varying channels

Abstract

A new method for blind maximum likelihood sequence estimation is proposed. The unknown channel time variations are decomposed using optimal unconditional bases such as orthonormal wavelet bases. We show that it is possible to represent the channel in a reduced order dimensional space by matching the scattering function of the multipath channel to its decomposition and obtain an approach to per-survivor processing that is effective in fast fading environments such as those practically found in macrocell wireless communication applications.