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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...

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Autores principales: Ramamoorthi, Yoghitha, Iwabuchi, Masashi, Murakami, Tomoki, Ogawa, Tomoaki, Takatori, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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