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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/17/6339 |
| _version_ | 1827665029080547328 |
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| author | Daniel Kraus Konrad Diwold Jesús Pestana Peter Priller Erich Leitgeb |
| author_facet | Daniel Kraus Konrad Diwold Jesús Pestana Peter Priller Erich Leitgeb |
| author_sort | Daniel Kraus |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T01:16:50Z |
| format | Article |
| id | doaj.art-2967b268453045a0a95946d81b428fb2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T01:16:50Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2967b268453045a0a95946d81b428fb22023-11-23T14:06:49ZengMDPI AGSensors1424-82202022-08-012217633910.3390/s22176339Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation EnvironmentsDaniel Kraus0Konrad Diwold1Jesús Pestana2Peter Priller3Erich Leitgeb4Pro2Future GmbH, 8010 Graz, AustriaPro2Future GmbH, 8010 Graz, AustriaPro2Future GmbH, 8010 Graz, AustriaAVL List GmbH, 8020 Graz, AustriaInstitute of Microwave and Photonic Engineering, Graz University of Technology, 8010 Graz, AustriaThis 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.https://www.mdpi.com/1424-8220/22/17/6339Bluetooth Low Energy (BLE)antennaswireless sensor networkrecommendation systemray tracing |
| spellingShingle | Daniel Kraus Konrad Diwold Jesús Pestana Peter Priller Erich Leitgeb Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments Sensors Bluetooth Low Energy (BLE) antennas wireless sensor network recommendation system ray tracing |
| 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 | Bluetooth Low Energy (BLE) antennas wireless sensor network recommendation system ray tracing |
| url | https://www.mdpi.com/1424-8220/22/17/6339 |
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