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Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments

This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and es...

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Autores principales: Kraus, Daniel, Diwold, Konrad, Pestana, Jesús, Priller, Peter, Leitgeb, Erich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460237/
https://www.ncbi.nlm.nih.gov/pubmed/36080797
http://dx.doi.org/10.3390/s22176339
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author Kraus, Daniel
Diwold, Konrad
Pestana, Jesús
Priller, Peter
Leitgeb, Erich
author_facet Kraus, Daniel
Diwold, Konrad
Pestana, Jesús
Priller, Peter
Leitgeb, Erich
author_sort Kraus, Daniel
collection PubMed
description This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and establish an antenna recommendation system for a specific harsh environment, i.e., an engine compartment of a vehicle. We propose the usage of electromagnetic (EM) and ray tracing simulations as a computationally cost-effective method to establish such a recommendation system, which we test by means of an experimental testbed—or test environment—that consists of both a physical, as well as its identical simulation, model. A pool of antennas is evaluated to identify and verify antenna behavior and properties at specified positions in the harsh environment. We use a vector network analyzer (VNA) for accurate measurements and a received signal strength indicator (RSSI) for a first estimation of system performance. Our analysis of the experimental measurements and its EM simulation counterparts shows that both types of data lead to equivalent antenna recommendations at each of the defined positions and experimental conditions. This evaluation and verification process by measurements on an experimental testbed is important to validate the antenna recommendation process. Our results indicate that—with properly characterized antennas—such measurements can be substituted with EM simulations on an accurate EM model, which can contribute to dramatically speeding up the antenna positioning and selection process.
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spelling pubmed-94602372022-09-10 Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments Kraus, Daniel Diwold, Konrad Pestana, Jesús Priller, Peter Leitgeb, Erich Sensors (Basel) Article This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and establish an antenna recommendation system for a specific harsh environment, i.e., an engine compartment of a vehicle. We propose the usage of electromagnetic (EM) and ray tracing simulations as a computationally cost-effective method to establish such a recommendation system, which we test by means of an experimental testbed—or test environment—that consists of both a physical, as well as its identical simulation, model. A pool of antennas is evaluated to identify and verify antenna behavior and properties at specified positions in the harsh environment. We use a vector network analyzer (VNA) for accurate measurements and a received signal strength indicator (RSSI) for a first estimation of system performance. Our analysis of the experimental measurements and its EM simulation counterparts shows that both types of data lead to equivalent antenna recommendations at each of the defined positions and experimental conditions. This evaluation and verification process by measurements on an experimental testbed is important to validate the antenna recommendation process. Our results indicate that—with properly characterized antennas—such measurements can be substituted with EM simulations on an accurate EM model, which can contribute to dramatically speeding up the antenna positioning and selection process. MDPI 2022-08-23 /pmc/articles/PMC9460237/ /pubmed/36080797 http://dx.doi.org/10.3390/s22176339 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
Kraus, Daniel
Diwold, Konrad
Pestana, Jesús
Priller, Peter
Leitgeb, Erich
Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title_full Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title_fullStr Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title_full_unstemmed Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title_short Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
title_sort towards a recommender system for in-vehicle antenna placement in harsh propagation environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460237/
https://www.ncbi.nlm.nih.gov/pubmed/36080797
http://dx.doi.org/10.3390/s22176339
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