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IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes
Passive technologies, including intelligent reflecting surfaces (IRS), are gaining traction thanks to their ability to enhance communication systems while maintaining minimal cost and low complexity. They can assist a wireless sensor network (WSN) by achieving low power requirements for sensors and...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737329/ https://www.ncbi.nlm.nih.gov/pubmed/36501931 http://dx.doi.org/10.3390/s22239229 |
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author | Alwazani, Hibatallah Chaaban, Anas |
author_facet | Alwazani, Hibatallah Chaaban, Anas |
author_sort | Alwazani, Hibatallah |
collection | PubMed |
description | Passive technologies, including intelligent reflecting surfaces (IRS), are gaining traction thanks to their ability to enhance communication systems while maintaining minimal cost and low complexity. They can assist a wireless sensor network (WSN) by achieving low power requirements for sensors and aid communication needs in many applications, for instance, environmental monitoring. In this paper, we propose an IRS-equipped WSN which describes sensors equipped with IRSs instead of active radio frequency (RF) electronics. The IRS sensor node (ISN) intercepts a dedicated signal from a power source such as a base station (BS) and modulates the transmission of that signal to an intended recipient. In order to enable multiple sensors to transmit to the receiver, we study opportunistic scheduling (OS) utilizing multi-sensor diversity while considering blind IRS operation, and compare it with round-robin (RR), proportional fairness (PF), and a theoretical upper bound. We study the effect of the choice of the number of IRS elements N and number of ISNs L on the average throughput of the system under OS. Finally, we provide pertinent comparisons for the different scheduling schemes and IRS configurations under relevant system performance metrics, highlighting different scenarios in which each scheme performs better. |
format | Online Article Text |
id | pubmed-9737329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97373292022-12-11 IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes Alwazani, Hibatallah Chaaban, Anas Sensors (Basel) Article Passive technologies, including intelligent reflecting surfaces (IRS), are gaining traction thanks to their ability to enhance communication systems while maintaining minimal cost and low complexity. They can assist a wireless sensor network (WSN) by achieving low power requirements for sensors and aid communication needs in many applications, for instance, environmental monitoring. In this paper, we propose an IRS-equipped WSN which describes sensors equipped with IRSs instead of active radio frequency (RF) electronics. The IRS sensor node (ISN) intercepts a dedicated signal from a power source such as a base station (BS) and modulates the transmission of that signal to an intended recipient. In order to enable multiple sensors to transmit to the receiver, we study opportunistic scheduling (OS) utilizing multi-sensor diversity while considering blind IRS operation, and compare it with round-robin (RR), proportional fairness (PF), and a theoretical upper bound. We study the effect of the choice of the number of IRS elements N and number of ISNs L on the average throughput of the system under OS. Finally, we provide pertinent comparisons for the different scheduling schemes and IRS configurations under relevant system performance metrics, highlighting different scenarios in which each scheme performs better. MDPI 2022-11-27 /pmc/articles/PMC9737329/ /pubmed/36501931 http://dx.doi.org/10.3390/s22239229 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 Alwazani, Hibatallah Chaaban, Anas IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title | IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title_full | IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title_fullStr | IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title_full_unstemmed | IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title_short | IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes |
title_sort | irs-enabled ultra-low-power wireless sensor networks: scheduling and transmission schemes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737329/ https://www.ncbi.nlm.nih.gov/pubmed/36501931 http://dx.doi.org/10.3390/s22239229 |
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