Parametrization of the local scattering function estimator for vehicular-to-vehicular channels
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1405663
- author
- Bernadó, Laura ; Zemen, Thomas ; Paier, Alexander ; Kåredal, Johan LU and Fleury, Bernard
- organization
- publishing date
- 2009
- 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}}, }