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

Author

Martone, Massimiliano

Author_Institution

Watkins-Johnson Co., Gaithersburg, MD, USA

fYear

1999

fDate

1999

Firstpage

255

Lastpage

258

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

Keywords

blind equalisers; cellular radio; discrete wavelet transforms; fading channels; maximum likelihood sequence estimation; multipath channels; time-varying channels; blind maximum likelihood sequence estimation; discrete wavelet transform; fast fading environments; macrocell wireless communication; multipath channel; orthonormal wavelet bases; per-survivor processing; reduced order dimensional space; scattering function; time-varying channels; unknown channel time variations; wavelet-based separating kernels; Adaptive algorithm; Convergence; Discrete wavelet transforms; Fading; Filters; Kernel; Maximum likelihood estimation; Scattering; Signal resolution; Time-varying channels;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Advances in Wireless Communications, 1999. SPAWC '99. 1999 2nd IEEE Workshop on

Conference_Location

Annapolis, MD

Print_ISBN

0-7803-5599-7

Type

conf

DOI

10.1109/SPAWC.1999.783067

Filename

783067