Placement optimization of multiple UAVs for energy-efficient maximal user coverage

This paper proposes a deterministic Global Optimization Algorithm (GOA) for UAV-assisted communications, developed as an enhancement to the benchmark Two-Stage Optimization Algorithm (TSOA). The algorithm simultaneously addresses the dual objectives of maximizing ground user (GU) coverage and minimizing total power consumption in multiple UAV systems. Unlike existing literature, which predominantly relies on heuristic approaches, GOA provides a more precise and systematic solution to achieve optimal performance. Comprehensive simulations demonstrate that GOA achieves a 3.68% increase in coverage count versus SOA under clustered GU distributions while delivering energy savings approximately 2.47% (uniform) and 2.6% (clustered) relative to the TSOA benchmark. Crucially, these efficiency gains are realized while maintaining superior GU coverage maximization versus all benchmarked methods. Both numerical results and visual analyses conclusively validate the proposed algorithm's outperformance of existing benchmarks. ©2025 The Korean Institute of Communications and Information Sciences. Publishing Services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

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Publication Details

Journal
ICT Express
Published
2025-10-10
DOI
https://doi.org/10.1016/j.icte.2025.10.003
Primary Topic
UAV Applications and Optimization
Type
article
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article

Placement optimization of multiple UAVs for energy-efficient maximal user coverage

Gourab Sen Gupta, Xiang Gui, Syed Faraz Hasan, Chen Zhang
ICT Express
UAV Applications and Optimization
article

Placement optimization of multiple UAVs for energy-efficient maximal user coverage

Gourab Sen Gupta, Xiang Gui, Syed Faraz Hasan, Chen Zhang
article en

Abstract

This paper proposes a deterministic Global Optimization Algorithm (GOA) for UAV-assisted communications, developed as an enhancement to the benchmark Two-Stage Optimization Algorithm (TSOA). The algorithm simultaneously addresses the dual objectives of maximizing ground user (GU) coverage and minimizing total power consumption in multiple UAV systems. Unlike existing literature, which predominantly relies on heuristic approaches, GOA provides a more precise and systematic solution to achieve optimal performance. Comprehensive simulations demonstrate that GOA achieves a 3.68% increase in coverage count versus SOA under clustered GU distributions while delivering energy savings approximately 2.47% (uniform) and 2.6% (clustered) relative to the TSOA benchmark. Crucially, these efficiency gains are realized while maintaining superior GU coverage maximization versus all benchmarked methods. Both numerical results and visual analyses conclusively validate the proposed algorithm's outperformance of existing benchmarks. ©2025 The Korean Institute of Communications and Information Sciences. Publishing Services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

ICT ExpressVol. 11(6)
Hebei University of Economics and Business (CN), Hebei University of Science and Technology (CN), Massey University (NZ), University of New England (AU)
Openalex Percentile: Top 62%
UAV Applications and Optimization
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Placement optimization of multiple UAVs for energy-efficient maximal user coverage — Gourab Sen Gupta, Xiang Gui, et al. · ICT Express (2025) | TGRS Research Map | TGRS