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Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model

Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in...

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Autores principales: Lopez-Fernandez, Jesus, Moreno-Pozas, Laureano, Lopez-Martinez, Francisco Javier, Martos-Naya, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970064/
https://www.ncbi.nlm.nih.gov/pubmed/27376293
http://dx.doi.org/10.3390/s16071014
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author Lopez-Fernandez, Jesus
Moreno-Pozas, Laureano
Lopez-Martinez, Francisco Javier
Martos-Naya, Eduardo
author_facet Lopez-Fernandez, Jesus
Moreno-Pozas, Laureano
Lopez-Martinez, Francisco Javier
Martos-Naya, Eduardo
author_sort Lopez-Fernandez, Jesus
collection PubMed
description Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in such scenarios. In this paper, we address the joint estimation of the parameters K and Δ that characterize the TWDP fading model, based on the observation of the received signal envelope. We use a moment-based approach to derive closed-form expressions for the estimators of K and Δ, as well as closed-form expressions for their asymptotic variance. Results show that the estimation error is close to the Cramer-Rao lower bound for a wide range of values of the parameters K and Δ. The performance degradation due to a finite number of observations is also analyzed.
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spelling pubmed-49700642016-08-04 Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model Lopez-Fernandez, Jesus Moreno-Pozas, Laureano Lopez-Martinez, Francisco Javier Martos-Naya, Eduardo Sensors (Basel) Article Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in such scenarios. In this paper, we address the joint estimation of the parameters K and Δ that characterize the TWDP fading model, based on the observation of the received signal envelope. We use a moment-based approach to derive closed-form expressions for the estimators of K and Δ, as well as closed-form expressions for their asymptotic variance. Results show that the estimation error is close to the Cramer-Rao lower bound for a wide range of values of the parameters K and Δ. The performance degradation due to a finite number of observations is also analyzed. MDPI 2016-06-30 /pmc/articles/PMC4970064/ /pubmed/27376293 http://dx.doi.org/10.3390/s16071014 Text en © 2016 by the authors; 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lopez-Fernandez, Jesus
Moreno-Pozas, Laureano
Lopez-Martinez, Francisco Javier
Martos-Naya, Eduardo
Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title_full Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title_fullStr Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title_full_unstemmed Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title_short Joint Parameter Estimation for the Two-Wave with Diffuse Power Fading Model
title_sort joint parameter estimation for the two-wave with diffuse power fading model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970064/
https://www.ncbi.nlm.nih.gov/pubmed/27376293
http://dx.doi.org/10.3390/s16071014
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