Parameter Estimation for Stochastic Channel Models using Temporal Moments

Ayush Bharti; Ramoni Adeogun; Troels Pedersen

doi:10.1109/APUSNCURSINRSM.2019.8888862

Parameter Estimation for Stochastic Channel Models using Temporal Moments

Ayush Bharti, Ramoni Adeogun, Troels Pedersen

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

10 Citationer (Scopus)

220 Downloads (Pure)

Abstract

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.

Originalsprog	Engelsk
Titel	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019
Antal sider	2
Forlag	IEEE
Publikationsdato	31 okt. 2019
Sider	1267-1268
Artikelnummer	8888862
ISBN (Trykt)	978-1-7281-0692-2, 978-1-7281-0692-2, 978-1-7281-0693-9
ISBN (Elektronisk)	978-1-7281-0692-2
DOI	https://doi.org/10.1109/APUSNCURSINRSM.2019.8888862
Status	Udgivet - 31 okt. 2019
Begivenhed	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting - Atlanta, USA, Atlanta, USA Varighed: 7 jul. 2019 → 12 jul. 2019 http://www.2019apsursi.org

Konference

Konference	2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
Lokation	Atlanta, USA
Land/Område	USA
By	Atlanta
Periode	07/07/2019 → 12/07/2019
Internetadresse	http://www.2019apsursi.org

Navn	I E E E Antennas and Propagation Society. International Symposium
ISSN	1522-3965

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10.1109/APUSNCURSINRSM.2019.8888862

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Citationsformater

@inproceedings{8921f76c8df6460fa3aab56536f64ab8,

title = "Parameter Estimation for Stochastic Channel Models using Temporal Moments",

abstract = "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.",

author = "Ayush Bharti and Ramoni Adeogun and Troels Pedersen",

year = "2019",

month = oct,

day = "31",

doi = "10.1109/APUSNCURSINRSM.2019.8888862",

language = "English",

isbn = " 978-1-7281-0692-2",

series = "I E E E Antennas and Propagation Society. International Symposium",

publisher = "IEEE",

pages = "1267--1268",

booktitle = "2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019",

address = "United States",

note = "2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APS-URSI ; Conference date: 07-07-2019 Through 12-07-2019",

url = "http://www.2019apsursi.org",

}

Bharti, A, Adeogun, R & Pedersen, T 2019, Parameter Estimation for Stochastic Channel Models using Temporal Moments. i 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019., 8888862, IEEE, I E E E Antennas and Propagation Society. International Symposium, s. 1267-1268, 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Atlanta, USA, 07/07/2019. https://doi.org/10.1109/APUSNCURSINRSM.2019.8888862

Parameter Estimation for Stochastic Channel Models using Temporal Moments. / Bharti, Ayush; Adeogun, Ramoni ; Pedersen, Troels.
2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019. IEEE, 2019. s. 1267-1268 8888862 (I E E E Antennas and Propagation Society. International Symposium).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Parameter Estimation for Stochastic Channel Models using Temporal Moments

AU - Bharti, Ayush

AU - Adeogun, Ramoni

AU - Pedersen, Troels

PY - 2019/10/31

Y1 - 2019/10/31

N2 - 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.

AB - 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.

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U2 - 10.1109/APUSNCURSINRSM.2019.8888862

DO - 10.1109/APUSNCURSINRSM.2019.8888862

M3 - Article in proceeding

SN - 978-1-7281-0692-2

SN - 978-1-7281-0693-9

T3 - I E E E Antennas and Propagation Society. International Symposium

SP - 1267

EP - 1268

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

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T2 - 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

Y2 - 7 July 2019 through 12 July 2019

ER -

Parameter Estimation for Stochastic Channel Models using Temporal Moments

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