Nowadays, at least two billion people are experiencing a complete lack of cellular coverage. Since the lack of cellular connectivity is mostly experienced in rural zones, it is of mandatory importance to design solutions to manage cellular architectures tailored to such zones. To this aim, we consider a new cellular 5G architecture, where the Base Stations (BSs) are carried by Unmanned Aerial Vehicles (UAVs). Specifically, we focus on the problem of planning the missions of the UAV-based BSs over the territory, with the goal of minimizing the energy consumed for moving the UAVs. After introducing the considered framework, which is based on a multi-period graph defined over a set of places and a set of Time Slots (TSs), we derive a simple algorithm, called GAUP, to solve the considered problem in a reasonable amount of time. Our results, obtained over a simple - yet representative - scenario, reveals that GAUP is able to efficiently manage the energy for moving the UAVs, while guaranteeing relatively low computation times.
Multi-Period Mission Planning of UAVs for 5G Coverage in Rural Areas: A Heuristic Approach / Jimenez, J. G.; Chiaraviglio, L.; Amorosi, L.; Blefari-Melazzi, N.. - (2018), pp. 52-59. (Intervento presentato al convegno 9th IEEE International Conference on the Network of the Future, NOF 2018 tenutosi a Poznan University of Technology, pol) [10.1109/NOF.2018.8598123].
Multi-Period Mission Planning of UAVs for 5G Coverage in Rural Areas: A Heuristic Approach
Amorosi L.;
2018
Abstract
Nowadays, at least two billion people are experiencing a complete lack of cellular coverage. Since the lack of cellular connectivity is mostly experienced in rural zones, it is of mandatory importance to design solutions to manage cellular architectures tailored to such zones. To this aim, we consider a new cellular 5G architecture, where the Base Stations (BSs) are carried by Unmanned Aerial Vehicles (UAVs). Specifically, we focus on the problem of planning the missions of the UAV-based BSs over the territory, with the goal of minimizing the energy consumed for moving the UAVs. After introducing the considered framework, which is based on a multi-period graph defined over a set of places and a set of Time Slots (TSs), we derive a simple algorithm, called GAUP, to solve the considered problem in a reasonable amount of time. Our results, obtained over a simple - yet representative - scenario, reveals that GAUP is able to efficiently manage the energy for moving the UAVs, while guaranteeing relatively low computation times.File | Dimensione | Formato | |
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