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Parametrization of the local scattering function estimator for vehicular-to-vehicular channels

Bernadó, Laura ; Zemen, Thomas ; Paier, Alexander ; Kåredal, Johan LU and Fleury, Bernard (2009) IEEE Vehicular Technology Conference (VTC2009-fall) p.1-5
Abstract
Non wide-sense stationary (WSS) uncorrelated scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square

error (MSE). For that purpose we use the structure of a twodimensional

Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters and the length of the stationarity regions on the MMSE. The analysis is performed... (More)
Non wide-sense stationary (WSS) uncorrelated scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square

error (MSE). For that purpose we use the structure of a twodimensional

Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters and the length of the stationarity regions on the MMSE. The analysis is performed considering

three different scenarios representing different scattering properties.

We show that there is an optimal combination of estimator parameters and length of stationarity region which provides a minimum MMSE. (Less)
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author
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organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
[Host publication title missing]
pages
5 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE Vehicular Technology Conference (VTC2009-fall)
conference location
Anchorage, AK, United States
conference dates
2009-09-20 - 2009-09-23
external identifiers
  • scopus:77951456463
language
English
LU publication?
yes
id
20f46461-0fb6-4f7e-aac6-d152a16f8f36 (old id 1405663)
date added to LUP
2016-04-04 11:37:27
date last changed
2022-01-29 22:09:32
@inproceedings{20f46461-0fb6-4f7e-aac6-d152a16f8f36,
  abstract     = {{Non wide-sense stationary (WSS) uncorrelated scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square<br/><br>
error (MSE). For that purpose we use the structure of a twodimensional<br/><br>
Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters and the length of the stationarity regions on the MMSE. The analysis is performed considering<br/><br>
three different scenarios representing different scattering properties.<br/><br>
We show that there is an optimal combination of estimator parameters and length of stationarity region which provides a minimum MMSE.}},
  author       = {{Bernadó, Laura and Zemen, Thomas and Paier, Alexander and Kåredal, Johan and Fleury, Bernard}},
  booktitle    = {{[Host publication title missing]}},
  language     = {{eng}},
  pages        = {{1--5}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Parametrization of the local scattering function estimator for vehicular-to-vehicular channels}},
  url          = {{https://lup.lub.lu.se/search/files/5817040/1528672.pdf}},
  year         = {{2009}},
}