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Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model

Two-wave with diffuse power (TWDP) is one of the most promising models for description of a small-scale fading effects in the emerging wireless networks. However, its conventional parameterization based on parameters K and [Formula: see text] is not in line with model’s underlying physical mechanism...

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Autores principales: Njemcevic, Pamela, Kaljic, Enio, Maric, Almir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838422/
https://www.ncbi.nlm.nih.gov/pubmed/35161524
http://dx.doi.org/10.3390/s22030774
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author Njemcevic, Pamela
Kaljic, Enio
Maric, Almir
author_facet Njemcevic, Pamela
Kaljic, Enio
Maric, Almir
author_sort Njemcevic, Pamela
collection PubMed
description Two-wave with diffuse power (TWDP) is one of the most promising models for description of a small-scale fading effects in the emerging wireless networks. However, its conventional parameterization based on parameters K and [Formula: see text] is not in line with model’s underlying physical mechanisms. Accordingly, in this paper, we first identified anomalies related to usage of conventional TWDP parameterization in moment-based estimation, showing that the existing [Formula: see text]-based estimators are unable to provide meaningful estimates in some channel conditions. Then, we derived moment-based estimators of recently introduced physically justified TWDP parameters K and [Formula: see text] and analyzed their performance through asymptotic variance (AsV) and Cramer–Rao bound (CRB) metrics. Performed analysis has shown that [Formula: see text]-based estimators managed to overcome all anomalies observed for [Formula: see text]-based estimators, simultaneously improving the overall moment-based estimation accuracy.
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spelling pubmed-88384222022-02-13 Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model Njemcevic, Pamela Kaljic, Enio Maric, Almir Sensors (Basel) Article Two-wave with diffuse power (TWDP) is one of the most promising models for description of a small-scale fading effects in the emerging wireless networks. However, its conventional parameterization based on parameters K and [Formula: see text] is not in line with model’s underlying physical mechanisms. Accordingly, in this paper, we first identified anomalies related to usage of conventional TWDP parameterization in moment-based estimation, showing that the existing [Formula: see text]-based estimators are unable to provide meaningful estimates in some channel conditions. Then, we derived moment-based estimators of recently introduced physically justified TWDP parameters K and [Formula: see text] and analyzed their performance through asymptotic variance (AsV) and Cramer–Rao bound (CRB) metrics. Performed analysis has shown that [Formula: see text]-based estimators managed to overcome all anomalies observed for [Formula: see text]-based estimators, simultaneously improving the overall moment-based estimation accuracy. MDPI 2022-01-20 /pmc/articles/PMC8838422/ /pubmed/35161524 http://dx.doi.org/10.3390/s22030774 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Njemcevic, Pamela
Kaljic, Enio
Maric, Almir
Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title_full Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title_fullStr Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title_full_unstemmed Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title_short Moment-Based Parameter Estimation for the Γ-Parameterized TWDP Model
title_sort moment-based parameter estimation for the γ-parameterized twdp model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838422/
https://www.ncbi.nlm.nih.gov/pubmed/35161524
http://dx.doi.org/10.3390/s22030774
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