Title
MMSE estimation of basis expansion models for rapidly time-varying channels
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 equal- izers. We rely on pilot symbol assisted modulation (PSAM) to estimate the channel (or the BEM coefficients of the chan- nel). 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 model- ing error, the latter is sensitive to noise. A robust channel estimation can then be obtained by combining the MMSE in- terpolation 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 oversam- pling rate equal to 2 appears to be sufficient), while only a slight improvement is obtained when the critically sampled Doppler spectrum is used.
Year
Venue
Keywords
2005
EUSIPCO
channel estimation,equalisers,interpolation,least mean squares methods,time-varying channels,bem channel estimation,bem coefficient,doppler spectrum,mmse estimation,mmse interpolation,psam,basis expansion model,channel equalizer,channel estimation technique,minimum mean-square error interpolation,pilot symbol assisted modulation,time-varying channel
Field
DocType
ISBN
Digital signal processing,Wireless,Oversampling,Control theory,Signal-to-noise ratio,Interpolation,Communication channel,Modulation,Doppler effect,Mathematics
Conference
978-160-4238-21-1
Citations 
PageRank 
References 
9
0.68
8
Authors
3
Name
Order
Citations
PageRank
Imad Barhumi156837.93
G. Leus24344307.24
Marc Moonen337746.79