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

Volume

3

Issue

3

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

78

Lastpage

80

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;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/4234.752908

Filename

752908