Optimizing Multi-UAV 3D Deployment for Energy-Efficient Sensing over Uneven Terrains

Moliya, Rushi, Patel, Dhaval K, Soni, Brijesh and Lopez-Benitez, Miguel ORCID: 0000-0003-0526-6687 (2025) Optimizing Multi-UAV 3D Deployment for Energy-Efficient Sensing over Uneven Terrains In: 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), 2026-1-9 - 2026-1-12.

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Abstract

In this work, we present a terrain-aware 3D multi-unmanned aerial vehicles (UAV) cooperative spectrum sensing (CSS) framework that jointly optimizes UAV placement and antenna orientation to maximize detection probability while minimizing hover energy. A bounding volume hierarchy (BVH)-based adaptive scheme is proposed for efficient line-of-sight (LoS) evaluation, and a hierarchical genetic algorithm (GA)-particle swarm optimization (PSO) approch is adopted to address the inherently non-convex bi-objective problem, achieving a balanced exploration of the search space while ensuring LoS connectivity and energy efficiency. Monte Carlo simulations using real terrain data demonstrate up to 37.02% improvement in detection probability and 48.90% reduction in hover energy compared to PSO-only baselines, confirming the practicality and effectiveness of the proposed framework for uneven terrain environments.

Item Type:	Conference Item (Unspecified)
Uncontrolled Keywords:	Unmanned aerial vehicles, cooperative spectrum sensing, eigenvalue-based detection, uneven terrain, genetic algorithm, particle swarm optimization.
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Computer Science & Informatics Faculty of Science & Engineering > School of Computer Science & Informatics > Trustworthy Computing
Depositing User:	Symplectic Admin
Date Deposited:	17 Nov 2025 08:42
Last Modified:	23 May 2026 11:16
DOI:	10.1109/CCNC65079.2026.11366444
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3195441
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