We target the problem of providing 5G network connectivity in rural zones by means of Base Stations (BSs) carried by Unmanned Aerial Vehicles (UAVs). Our goal is to schedule the UAVs missions to: i) limit the amount of energy consumed by each UAV, ii) ensure the coverage of selected zones over the territory, ii) decide where and when each UAV has to be recharged in a ground site, iii) deal with the amount of energy provided by Solar Panels (SPs) and batteries installed in each ground site. We then formulate the RURALPLAN optimization problem, a variant of the unsplittable multicommodity flow problem defined on a multiperiod graph. After detailing the objective function and the constraints, we solve RURALPLAN in a realistic scenario. Results show that RURALPLAN is able to outperform a solution ensuring coverage but not considering the energy management of the UAVs.
Energy-efficient mission planning of UAVs for 5G coverage in rural zones / Amorosi, Lavinia; Chiaraviglio, Luca; D'Andreagiovanni, Fabio; Blefari-Melazzi, Nicola. - ELETTRONICO. - (2018), pp. 1-9. (Intervento presentato al convegno IEEE International Conference on Environmental Engineering (EE) tenutosi a Milan, Italy) [10.1109/EE1.2018.8385250].
Energy-efficient mission planning of UAVs for 5G coverage in rural zones
Lavinia Amorosi
;
2018
Abstract
We target the problem of providing 5G network connectivity in rural zones by means of Base Stations (BSs) carried by Unmanned Aerial Vehicles (UAVs). Our goal is to schedule the UAVs missions to: i) limit the amount of energy consumed by each UAV, ii) ensure the coverage of selected zones over the territory, ii) decide where and when each UAV has to be recharged in a ground site, iii) deal with the amount of energy provided by Solar Panels (SPs) and batteries installed in each ground site. We then formulate the RURALPLAN optimization problem, a variant of the unsplittable multicommodity flow problem defined on a multiperiod graph. After detailing the objective function and the constraints, we solve RURALPLAN in a realistic scenario. Results show that RURALPLAN is able to outperform a solution ensuring coverage but not considering the energy management of the UAVs.File | Dimensione | Formato | |
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