{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T07:52:17Z","timestamp":1774338737223,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T00:00:00Z","timestamp":1640736000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 multi-UAV 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\u2019 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 \u22481\/17 and \u22481\/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.<\/jats:p>","DOI":"10.3390\/s22010223","type":"journal-article","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T08:12:15Z","timestamp":1640765535000},"page":"223","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Power-Efficient Wireless Coverage Using Minimum Number of UAVs"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7040-8963","authenticated-orcid":false,"given":"Ahmad","family":"Sawalmeh","sequence":"first","affiliation":[{"name":"Computer Science Department, Northern Border University, Arar 91431, Saudi Arabia"},{"name":"Remote Sensing Unit, Northern Border University, Arar 91431, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1849-6687","authenticated-orcid":false,"given":"Noor Shamsiah","family":"Othman","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7620-5836","authenticated-orcid":false,"given":"Guanxiong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Newark College of Engineering, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1583-713X","authenticated-orcid":false,"given":"Abdallah","family":"Khreishah","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Newark College of Engineering, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8469-880X","authenticated-orcid":false,"given":"Ali","family":"Alenezi","sequence":"additional","affiliation":[{"name":"Remote Sensing Unit, Northern Border University, Arar 91431, Saudi Arabia"},{"name":"Electrical Engineering Department, Northern Border University, Arar 91431, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3932-3814","authenticated-orcid":false,"given":"Abdulaziz","family":"Alanazi","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Northern Border University, Arar 91431, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"48572","DOI":"10.1109\/ACCESS.2019.2909530","article-title":"Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges","volume":"7","author":"Shakhatreh","year":"2019","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1109\/MWC.2018.1800023","article-title":"Cellular-connected UAV: Potential, challenges, and promising technologies","volume":"26","author":"Zeng","year":"2018","journal-title":"IEEE Wirel. 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