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Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications

Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designi...

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Autores principales: Cai, Bowen, Zhang, Qianqian, Ge, Jungang, Xie, Weiliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144711/
https://www.ncbi.nlm.nih.gov/pubmed/37112217
http://dx.doi.org/10.3390/s23083875
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author Cai, Bowen
Zhang, Qianqian
Ge, Jungang
Xie, Weiliang
author_facet Cai, Bowen
Zhang, Qianqian
Ge, Jungang
Xie, Weiliang
author_sort Cai, Bowen
collection PubMed
description Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designing satellites, it is difficult to launch a dedicated satellite for IoT communications. To facilitate IoT communications over LEO SatCom, in this paper, we propose the cognitive LEO satellite system, where the IoT users act as the secondary user to access the legacy LEO satellites and cognitively use the spectrum of the legacy LEO users. Due to the flexibility of code division multiple access (CDMA) in multiple access and the wide use of CDMA in LEO SatCom, we apply CDMA to support cognitive satellite IoT communications. For the cognitive LEO satellite system, we are interested in the achievable rate analysis and resource allocation. Specifically, considering the randomness of spreading codes, we use the random matrix theory to analyze the asymptotic signal-to-interference-plus-noise ratios (SINRs) and accordingly obtain the achievable rates for both legacy and IoT systems. The power of the legacy and IoT transmissions at the receiver are jointly allocated to maximize the sum rate of the IoT transmission subject to the legacy satellite system performance requirement and the maximum received power constraints. We prove that the sum rate of the IoT users is quasi-concave over the satellite terminal receive power, based on which the optimal receive powers for these two systems are derived. Finally, the resource allocation scheme proposed in this paper has been verified by extensive simulations.
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spelling pubmed-101447112023-04-29 Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications Cai, Bowen Zhang, Qianqian Ge, Jungang Xie, Weiliang Sensors (Basel) Article Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designing satellites, it is difficult to launch a dedicated satellite for IoT communications. To facilitate IoT communications over LEO SatCom, in this paper, we propose the cognitive LEO satellite system, where the IoT users act as the secondary user to access the legacy LEO satellites and cognitively use the spectrum of the legacy LEO users. Due to the flexibility of code division multiple access (CDMA) in multiple access and the wide use of CDMA in LEO SatCom, we apply CDMA to support cognitive satellite IoT communications. For the cognitive LEO satellite system, we are interested in the achievable rate analysis and resource allocation. Specifically, considering the randomness of spreading codes, we use the random matrix theory to analyze the asymptotic signal-to-interference-plus-noise ratios (SINRs) and accordingly obtain the achievable rates for both legacy and IoT systems. The power of the legacy and IoT transmissions at the receiver are jointly allocated to maximize the sum rate of the IoT transmission subject to the legacy satellite system performance requirement and the maximum received power constraints. We prove that the sum rate of the IoT users is quasi-concave over the satellite terminal receive power, based on which the optimal receive powers for these two systems are derived. Finally, the resource allocation scheme proposed in this paper has been verified by extensive simulations. MDPI 2023-04-11 /pmc/articles/PMC10144711/ /pubmed/37112217 http://dx.doi.org/10.3390/s23083875 Text en © 2023 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
Cai, Bowen
Zhang, Qianqian
Ge, Jungang
Xie, Weiliang
Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title_full Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title_fullStr Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title_full_unstemmed Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title_short Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
title_sort resource allocation for cognitive leo satellite systems: facilitating iot communications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144711/
https://www.ncbi.nlm.nih.gov/pubmed/37112217
http://dx.doi.org/10.3390/s23083875
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