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.
IEEE International Conference on Environmental Engineering (EE)
batteries; 5G mobile communication; energy states; unmanned aerial vehicles; computer architecture; optimization; internet
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
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].
File allegati a questo prodotto
File Dimensione Formato  
Amorosi_energy-efficient-mission_2018.pdf

solo gestori archivio

Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.36 MB
Formato Adobe PDF
3.36 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1121197
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 39
  • ???jsp.display-item.citation.isi??? 28
social impact