MMSE estimation of basis expansion models for rapidly time-varying channels

Imad Barhumi, Geert Leus, Marc Moonen

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

14 Citations (Scopus)

Abstract

In this paper, we propose an estimation technique for rapidly time-varying channels. We approximate the time-varying channel using the basis expansion model (BEM). The BEM coefficients of the channel are needed to design channel equalizers. We rely on pilot symbol assisted modulation (PSAM) to estimate the channel (or the BEM coefficients of the channel). We first derive the optimal minimum mean-square error (MMSE) interpolation based channel estimation technique. We then derive the BEM channel estimation, where only the BEM coefficients are estimated. We consider a BEM with a critically sampled Doppler spectrum, as well as a BEM with an oversampled Doppler spectrum. It has been shown that, while the first suffers from an error floor due to a modeling error, the latter is sensitive to noise. A robust channel estimation can then be obtained by combining the MMSE interpolation based channel estimation and the BEM channel estimation technique. Through computer simulations, it is shown that the resulting algorithm provides a significant gain when an oversampled Doppler spectrum is used (an oversampling rate equal to 2 appears to be sufficient), while only a slight improvement is obtained when the critically sampled Doppler spectrum is used.

Original languageEnglish
Title of host publication13th European Signal Processing Conference, EUSIPCO 2005
Pages1728-1732
Number of pages5
Publication statusPublished - Dec 1 2005
Externally publishedYes
Event13th European Signal Processing Conference, EUSIPCO 2005 - Antalya, Turkey
Duration: Sep 4 2005Sep 8 2005

Publication series

Name13th European Signal Processing Conference, EUSIPCO 2005

Other

Other13th European Signal Processing Conference, EUSIPCO 2005
Country/TerritoryTurkey
CityAntalya
Period9/4/059/8/05

ASJC Scopus subject areas

  • Signal Processing

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