DocumentCode :
3010749
Title :
Complexity reduction for vehicular channel estimation using the filter divergence measure
Author :
Bernadó, Laura ; Zemen, Thomas ; Paier, Alexander ; Karedal, Johan
Author_Institution :
ftw. Forschungszentrum Telekommunikation Wien, Vienna, Austria
fYear :
2010
fDate :
7-10 Nov. 2010
Firstpage :
141
Lastpage :
145
Abstract :
A key component in vehicular communications systems is the channel estimation filter that suppresses the additive noise in the channel estimates from pilot symbols. A filter which offers the best performance in terms of mean square error (MSE) is the well known Wiener filter. A drawback of using filters based on second order statistics is that they have to be recalculated when the statistical properties of the channel have changed. In vehicular communications the observed channels do not follow the wide-sense stationary (WSS) uncorrelated-scattering (US) properties, and therefore their power spectral density varies over time. A non-stationary process can be divided in time into consecutive stationarity regions where the WSS and US properties are assumed to hold, allowing to calculate the coefficients of a Wiener filter. In this paper we analyze the increase of the MSE observed when using a mismatched Wiener filter. The mismatch results from using the filter coefficients calculated for a past stationarity region. We relate this concept of performance degradation to spectral distance metrics. We use the spectral divergence between scattering functions at different time instances. Furthermore, we introduce a new metric, the filter divergence, which takes noise into account. We show that, by accepting an increase of MSE, the same filter coefficients can be used for several time regions, which allows computational complexity reduction in a real system.
Keywords :
Wiener filters; channel estimation; computational complexity; higher order statistics; mean square error methods; mobile radio; MSE; Wiener filter; complexity reduction; computational complexity reduction; filter divergence measure; mean square error; performance degradation; power spectral density; second order statistics; spectral distance metrics; spectral divergence; vehicular channel estimation filter; vehicular communications systems; wide-sense stationary uncorrelated-scattering property; Channel estimation; Degradation; Delay; Signal to noise ratio; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4244-9722-5
Type :
conf
DOI :
10.1109/ACSSC.2010.5757485
Filename :
5757485
Link To Document :
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