Drones as Mobile 5G Base Stations with Expanding Coverage in Remote Areas

• Published in: Iranian Journal of Information Processing & Management
• Main Authors: Laith S. Ismail, Sarah Haitham Jameel, Kuduev Altynbek Zhalilbekovich, Saad Jabbar Abbas, Ali Alsaray
• Format: Article
• Language: Persian
• Published: Iranian Research Institute for Information and Technology 2025-07-01
• Subjects: keywords: drones; unmanned aerial vehicle (uav); 5g; remote areas; deployment algorithms; particle swarm optimization (pso); grey wolf optimization (gwo); energy efficiency; coverage; mobile networks
• Online Access: https://jipm.irandoc.ac.ir/article_728308_51aa7c443082812be1f7b2ed98783cf6.pdf
• ISSN: 2251-8223; 2251-8231

ABSTRACTBackground: The rapid development of fifth-generation (5G) networks highlights challenges in extending coverage to remote and underserved areas due to infrastructure limitations and cost constraints. UAVs (drones) equipped with 5G base stations emerge as an innovative solution to this problem.Objective: This study aims to analyze the potential of drones as mobile 5G base stations to enhance connectivity in remote regions, addressing challenges like optimal deployment, energy efficiency, and user coverage.Methods: The research utilizes algorithms like Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for placement and energy management of drone-based 5G stations. Simulation models were employed to test these algorithms, with key metrics including coverage efficiency and energy consumption.Results: The study shows that drone-based stations can significantly improve coverage in remote areas, achieving up to 95% user coverage with optimized algorithms. Tethered drones and advanced energy management strategies were instrumental in enhancing endurance.Conclusion: Drones as mobile 5G base stations present a feasible and scalable approach to bridging the digital divide in remote regions. However, energy and regulatory challenges remain critical areas for future research.