Title :
Wavelet-based separating kernels for sequence estimation with unknown rapidly time-varying channels
Author :
Martone, Massimiliano
Author_Institution :
Telecommun. Group, Watkins-Johnson Co., Gaithersburg, MD, USA
fDate :
3/1/1999 12:00:00 AM
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. It is shown 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.
Keywords :
adaptive estimation; cellular radio; fading channels; maximum likelihood sequence estimation; multipath channels; signal representation; signal resolution; time-varying channels; wavelet transforms; adaptive algorithm; blind maximum-likelihood sequence estimation; channel representation; channel time variations; fast fading environments; macrocell wireless communication applications; multipath channel; multiresolution representation; optimal unconditional bases; orthonormal wavelet bases; per-survivor processing; rapidly time-varying channels; reduced-order dimensional space; scattering function; wavelet-based separating kernels; Adaptive algorithm; Discrete wavelet transforms; Fading; Filters; Frequency estimation; Kernel; Maximum likelihood estimation; Multipath channels; Scattering; Time-varying channels;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/4234.752908
