Blind identification of time-varying channels using second-order statistics

Michail K. Tsatsanis, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Novel linear algorithms are proposed in this paper for estimating symbol spaced, time-varying FIR communication channels, without resorting to higher-order statistics. The proposed methods are applicable to channels where each time-varying tap coefficient can be described (with respect to time) as a linear combination of a finite number of basis functions. Examples of such channels include periodically varying ones or channels locally modeled by a truncated Taylor series or wavelet expansion. It is shown that the estimation of the basis expansion parameters is equivalent to estimating the parameters of an FIR single-input-many-outputs (SIMO) system. By exploiting this equivalence, a number of different blind subspace methods are applicable, which have been originally developed in the context of SIMO systems. Identifiability issues are investigated and some illustrative simulations are presented.

Original languageEnglish (US)
Title of host publicationConference Record of the 29th Asilomar Conference on Signals, Systems and Computers, ACSSC 1995
EditorsAvtar Singh
PublisherIEEE Computer Society
Pages162-166
Number of pages5
ISBN (Electronic)0818673702
DOIs
StatePublished - Jan 1 1995
Externally publishedYes
Event29th Asilomar Conference on Signals, Systems and Computers, ACSSC 1995 - Pacific Grove, United States
Duration: Oct 30 1995Nov 1 1995

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume1
ISSN (Print)1058-6393

Conference

Conference29th Asilomar Conference on Signals, Systems and Computers, ACSSC 1995
CountryUnited States
CityPacific Grove
Period10/30/9511/1/95

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