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Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity
The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagne...
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/PMC9370838/ https://www.ncbi.nlm.nih.gov/pubmed/35957310 http://dx.doi.org/10.3390/s22155755 |
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author | Ramamoorthi, Yoghitha Iwabuchi, Masashi Murakami, Tomoki Ogawa, Tomoaki Takatori, Yasushi |
author_facet | Ramamoorthi, Yoghitha Iwabuchi, Masashi Murakami, Tomoki Ogawa, Tomoaki Takatori, Yasushi |
author_sort | Ramamoorthi, Yoghitha |
collection | PubMed |
description | The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an [Formula: see text]-fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems. |
format | Online Article Text |
id | pubmed-9370838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93708382022-08-12 Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity Ramamoorthi, Yoghitha Iwabuchi, Masashi Murakami, Tomoki Ogawa, Tomoaki Takatori, Yasushi Sensors (Basel) Article The next generation 6G wireless systems are envisioned to have higher reliability and capacity than the existing cellular systems. The reconfigurable intelligent surfaces (RISs)-assisted wireless networks are one of the promising solutions to control the wireless channel by altering the electromagnetic properties of the signal. The dual connectivity (DC) increases the per-user throughput by utilizing radio resources from two different base stations. In this work, we propose the RIS-assisted DC system to improve the per-user throughput of the users by utilizing resources from two base stations (BSs) in proximity via different RISs. Given an [Formula: see text]-fair utility function, the joint resource allocation and the user scheduling of a RIS-assisted DC system is formulated as an optimization problem and the optimal user scheduling time fraction is derived. A heuristic is proposed to solve the formulated optimization problem with the derived optimal user scheduling time fractions. Exhaustive simulation results for coverage and throughput of the RIS-assisted DC system are presented with varying user, BS, blockage, and RIS densities for different fairness values. Further, we show that the proposed RIS-assisted DC system provides significant throughput gain of 52% and 48% in certain scenarios when compared to the existing benchmark and DC systems. MDPI 2022-08-01 /pmc/articles/PMC9370838/ /pubmed/35957310 http://dx.doi.org/10.3390/s22155755 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 Ramamoorthi, Yoghitha Iwabuchi, Masashi Murakami, Tomoki Ogawa, Tomoaki Takatori, Yasushi Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title | Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title_full | Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title_fullStr | Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title_full_unstemmed | Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title_short | Resource Allocation for Reconfigurable Intelligent Surface Assisted Dual Connectivity |
title_sort | resource allocation for reconfigurable intelligent surface assisted dual connectivity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370838/ https://www.ncbi.nlm.nih.gov/pubmed/35957310 http://dx.doi.org/10.3390/s22155755 |
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