A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network
The exploitation of unmanned aerial vehicles (UAVs) in enhancing network performance in the context of beyond-fifth-generation (5G) communications has shown a variety of benefits compared to terrestrial counterparts. In addition, they have been largely conceived to play a central role in data dissem...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Communications and Networks |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frcmn.2024.1337697/full |
| _version_ | 1797295147580391424 |
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| author | Harris K. Armeniakos Konstantinos Maliatsos Petros S. Bithas Athanasios G. Kanatas |
| author_facet | Harris K. Armeniakos Konstantinos Maliatsos Petros S. Bithas Athanasios G. Kanatas |
| author_sort | Harris K. Armeniakos |
| collection | DOAJ |
| description | The exploitation of unmanned aerial vehicles (UAVs) in enhancing network performance in the context of beyond-fifth-generation (5G) communications has shown a variety of benefits compared to terrestrial counterparts. In addition, they have been largely conceived to play a central role in data dissemination to Internet of Things (IoT) devices. In the proposed work, a novel stochastic geometry unified framework is proposed to study the downlink performance in a UAV-assisted IoT network that integrates both UAV-base stations (UAV-BSs) and terrestrial IoT receiving devices. The framework builds upon the concept of the aerial UAV corridor, which is modeled as a finite line above the IoT network, and the one-dimensional (1D) binomial point process (BPP) is employed for modeling the spatial locations of the UAV-BSs in the aerial corridor. Subsequently, a comprehensive SNR-based performance analysis in terms of coverage probability, average rate, and energy efficiency is conducted under three association strategies, namely, the nth nearest-selection scheme, the random selection scheme, and the joint transmission coordinated multi-point (JT-CoMP) scheme. The numerical results reveal valuable system-level insights and trade-offs and provide a firm foundation for the design of UAV-assisted IoT networks. |
| first_indexed | 2024-03-07T21:42:32Z |
| format | Article |
| id | doaj.art-6c5e81fb05614626a2e3f586c349c809 |
| institution | Directory Open Access Journal |
| issn | 2673-530X |
| language | English |
| last_indexed | 2024-03-07T21:42:32Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Communications and Networks |
| spelling | doaj.art-6c5e81fb05614626a2e3f586c349c8092024-02-26T04:50:53ZengFrontiers Media S.A.Frontiers in Communications and Networks2673-530X2024-02-01510.3389/frcmn.2024.13376971337697A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT networkHarris K. Armeniakos0Konstantinos Maliatsos1Petros S. Bithas2Athanasios G. Kanatas3Department of Digital Systems, University of Piraeus, Piraeus, GreeceDepartment of Information and Communication Systems Engineering, School of Engineering, University of the Aegean, Samos, GreeceDepartment of Digital Industry Technologies, National and Kapodistrian University of Athens, Athens, GreeceDepartment of Digital Systems, University of Piraeus, Piraeus, GreeceThe exploitation of unmanned aerial vehicles (UAVs) in enhancing network performance in the context of beyond-fifth-generation (5G) communications has shown a variety of benefits compared to terrestrial counterparts. In addition, they have been largely conceived to play a central role in data dissemination to Internet of Things (IoT) devices. In the proposed work, a novel stochastic geometry unified framework is proposed to study the downlink performance in a UAV-assisted IoT network that integrates both UAV-base stations (UAV-BSs) and terrestrial IoT receiving devices. The framework builds upon the concept of the aerial UAV corridor, which is modeled as a finite line above the IoT network, and the one-dimensional (1D) binomial point process (BPP) is employed for modeling the spatial locations of the UAV-BSs in the aerial corridor. Subsequently, a comprehensive SNR-based performance analysis in terms of coverage probability, average rate, and energy efficiency is conducted under three association strategies, namely, the nth nearest-selection scheme, the random selection scheme, and the joint transmission coordinated multi-point (JT-CoMP) scheme. The numerical results reveal valuable system-level insights and trade-offs and provide a firm foundation for the design of UAV-assisted IoT networks.https://www.frontiersin.org/articles/10.3389/frcmn.2024.1337697/fullenergy efficiencyinternet of thingsjoint transmission coordinated multi-pointperformance analysisstochastic geometryunmanned aerial vehicle |
| spellingShingle | Harris K. Armeniakos Konstantinos Maliatsos Petros S. Bithas Athanasios G. Kanatas A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network Frontiers in Communications and Networks energy efficiency internet of things joint transmission coordinated multi-point performance analysis stochastic geometry unmanned aerial vehicle |
| title | A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network |
| title_full | A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network |
| title_fullStr | A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network |
| title_full_unstemmed | A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network |
| title_short | A stochastic geometry-based performance analysis of a UAV corridor-assisted IoT network |
| title_sort | stochastic geometry based performance analysis of a uav corridor assisted iot network |
| topic | energy efficiency internet of things joint transmission coordinated multi-point performance analysis stochastic geometry unmanned aerial vehicle |
| url | https://www.frontiersin.org/articles/10.3389/frcmn.2024.1337697/full |
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