Paper Info
Title
Optimal Energy Management of UAV-Based Cellular Networks Powered by Solar Panels and Batteries: Formulation and Solutions
Abstract
We focus on the problem of managing the energy consumption of a cellular network tailored to cover rural and low-income areas. The considered architecture exploits Unmanned Aerial Vehicles (UAVs) to ensure wireless coverage, as well as Solar Panels (SPs) and batteries installed in a set of ground sites, which provides the energy required to recharge the UAVs. We then target the maximization of the energy stored in the UAVs and in the ground sites, by ensuring the coverage of the territory through the scheduling of the UAV missions over space and time. After providing the problem formulation, we face its complexity by proposing a decomposition-based approach and by designing a brand-new genetic algorithm. The results, obtained over a set of representative case studies, reveal that there exists a trade-off between the UAVs battery level, the ground sites battery level, and the level of coverage. In addition, both the decomposed version and the genetic algorithm perform sufficiently close to the integrated model, with a strong improvement in the computation times.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2913448
IEEE ACCESS
Keywords
Field
DocType
Energy management,mixed integer linear programming,renewable energy sources,Unmanned Aerial Vehicles,UAV mission scheduling,cellular networks
Energy management,Wireless,Scheduling (computing),Computer science,Schedule,Cellular network,Battery (electricity),Energy consumption,Genetic algorithm,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
1
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Lavinia Amorosi173.32
Luca Chiaraviglio276855.95
Jaime Galán-Jiménez32811.00