Parameter Estimation for Stochastic Channel Models using Temporal Moments

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Resumé

This paper proposes a method to infer on the
parameters of a stochastic channel model from observations of
temporal moments without multipath extraction. The distribution
of the temporal moments is approximated to be Gaussian,
and sampling is carried out from the approximate posterior.
The temporal moments are found to be informative about the
model parameters, as the parameters can be recovered from the
samples.
OriginalsprogEngelsk
TitelProceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
Publikationsdato2019
StatusAccepteret/In press - 2019
Begivenhed2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting - Atlanta, USA, Atlanta, USA
Varighed: 7 jul. 201912 jul. 2019
http://www.2019apsursi.org

Konference

Konference2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
LokationAtlanta, USA
LandUSA
ByAtlanta
Periode07/07/201912/07/2019
Internetadresse

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Parameter estimation
Sampling

Citer dette

Bharti, A., Adeogun, R., & Pedersen, T. (Accepteret/In press). Parameter Estimation for Stochastic Channel Models using Temporal Moments. I Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
Bharti, Ayush ; Adeogun, Ramoni ; Pedersen, Troels. / Parameter Estimation for Stochastic Channel Models using Temporal Moments. Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. 2019.
@inproceedings{8921f76c8df6460fa3aab56536f64ab8,
title = "Parameter Estimation for Stochastic Channel Models using Temporal Moments",
abstract = "This paper proposes a method to infer on theparameters of a stochastic channel model from observations oftemporal moments without multipath extraction. The distributionof the temporal moments is approximated to be Gaussian,and sampling is carried out from the approximate posterior.The temporal moments are found to be informative about themodel parameters, as the parameters can be recovered from thesamples.",
author = "Ayush Bharti and Ramoni Adeogun and Troels Pedersen",
year = "2019",
language = "English",
booktitle = "Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting",

}

Bharti, A, Adeogun, R & Pedersen, T 2019, Parameter Estimation for Stochastic Channel Models using Temporal Moments. i Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting., Atlanta, USA, 07/07/2019.

Parameter Estimation for Stochastic Channel Models using Temporal Moments. / Bharti, Ayush; Adeogun, Ramoni; Pedersen, Troels.

Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. 2019.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Parameter Estimation for Stochastic Channel Models using Temporal Moments

AU - Bharti, Ayush

AU - Adeogun, Ramoni

AU - Pedersen, Troels

PY - 2019

Y1 - 2019

N2 - This paper proposes a method to infer on theparameters of a stochastic channel model from observations oftemporal moments without multipath extraction. The distributionof the temporal moments is approximated to be Gaussian,and sampling is carried out from the approximate posterior.The temporal moments are found to be informative about themodel parameters, as the parameters can be recovered from thesamples.

AB - This paper proposes a method to infer on theparameters of a stochastic channel model from observations oftemporal moments without multipath extraction. The distributionof the temporal moments is approximated to be Gaussian,and sampling is carried out from the approximate posterior.The temporal moments are found to be informative about themodel parameters, as the parameters can be recovered from thesamples.

M3 - Article in proceeding

BT - Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

ER -

Bharti A, Adeogun R, Pedersen T. Parameter Estimation for Stochastic Channel Models using Temporal Moments. I Proceedings 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. 2019