Power-efficient wireless coverage using minimum number of uavs
Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wi...
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my.uniten.dspace-272852023-05-29T17:42:08Z Power-efficient wireless coverage using minimum number of uavs Sawalmeh A. Othman N.S. Liu G. Khreishah A. Alenezi A. Alanazi A. 57194440590 56426823300 56597060900 24776009900 57221753256 57191531115 Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices Unmanned aerial vehicles (UAVs) can be deployed as backup aerial base stations due to cellular outage either during or post natural disaster. In this paper, an approach involving multiUAV three-dimensional (3D) deployment with power-efficient planning was proposed with the objective of minimizing the number of UAVs used to provide wireless coverage to all outdoor and indoor users that minimizes the required UAV transmit power and satisfies users� required data rate. More specifically, the proposed algorithm iteratively invoked a clustering algorithm and an efficient UAV 3D placement algorithm, which aimed for maximum wireless coverage using the minimum number of UAVs while minimizing the required UAV transmit power. Two scenarios where users are uniformly and non-uniformly distributed were considered. The proposed algorithm that employed a Particle Swarm Optimization (PSO)-based clustering algorithm resulted in a lower number of UAVs needed to serve all users compared with that when a K-means clustering algorithm was employed. Furthermore, the proposed algorithm that iteratively invoked a PSO-based clustering algorithm and PSO-based efficient UAV 3D placement algorithms reduced the execution time by a factor of ?1/17 and ?1/79, respectively, compared to that when the Genetic Algorithm (GA)-based and Artificial Bees Colony (ABC)-based efficient UAV 3D placement algorithms were employed. For the uniform distribution scenario, it was observed that the proposed algorithm required six UAVs to ensure 100% user coverage, whilst the benchmarker algorithm that utilized Circle Packing Theory (CPT) required five UAVs but at the expense of 67% of coverage density. � 2021 by the authors. Licensee MDPI, Basel, Switzerland. Final 2023-05-29T09:42:08Z 2023-05-29T09:42:08Z 2022 Article 10.3390/s22010223 2-s2.0-85121781389 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121781389&doi=10.3390%2fs22010223&partnerID=40&md5=58e7b378700d3139c0cb6935157cdcce https://irepository.uniten.edu.my/handle/123456789/27285 22 1 223 All Open Access, Gold, Green MDPI Scopus |
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| description |
Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices |
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57194440590 |
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57194440590 Sawalmeh A. Othman N.S. Liu G. Khreishah A. Alenezi A. Alanazi A. |
| format |
Article |
| author |
Sawalmeh A. Othman N.S. Liu G. Khreishah A. Alenezi A. Alanazi A. |
| spellingShingle |
Sawalmeh A. Othman N.S. Liu G. Khreishah A. Alenezi A. Alanazi A. Power-efficient wireless coverage using minimum number of uavs |
| author_sort |
Sawalmeh A. |
| title |
Power-efficient wireless coverage using minimum number of uavs |
| title_short |
Power-efficient wireless coverage using minimum number of uavs |
| title_full |
Power-efficient wireless coverage using minimum number of uavs |
| title_fullStr |
Power-efficient wireless coverage using minimum number of uavs |
| title_full_unstemmed |
Power-efficient wireless coverage using minimum number of uavs |
| title_sort |
power-efficient wireless coverage using minimum number of uavs |
| publisher |
MDPI |
| publishDate |
2023 |
| _version_ |
1806427811851796480 |
| score |
13.222552 |