Energy and Quality Aware Multi-UAV Flight Path Design Through Q-Learning Algorithms - Wired/Wireless Internet Communications Access content directly
Conference Papers Year : 2019

Energy and Quality Aware Multi-UAV Flight Path Design Through Q-Learning Algorithms

Abstract

We address the problem of devising an optimized energy aware flight plan for multiple Unmanned Aerial Vehicles (UAVs) mounted Base Stations (BS) within heterogeneous networks. The chosen approach makes use of Q-learning algorithms, through the definition of a reward related to relevant quality and battery consumption metrics, providing also service overlapping avoidance between UAVs, that is two or more UAVs serving the same cluster area. Numerical simulations and different training show the effectiveness of the devised flight paths in improving the general quality of the heterogeneous network users.
Fichier principal
Vignette du fichier
481347_1_En_20_Chapter.pdf (962.71 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02881735 , version 1 (26-06-2020)

Licence

Attribution

Identifiers

Cite

Hend Zouaoui, Simone Faricelli, Francesca Cuomo, Stefania Colonnese, Luca Chiaraviglio. Energy and Quality Aware Multi-UAV Flight Path Design Through Q-Learning Algorithms. 17th International Conference on Wired/Wireless Internet Communication (WWIC), Jun 2019, Bologna, Italy. pp.246-257, ⟨10.1007/978-3-030-30523-9_20⟩. ⟨hal-02881735⟩
31 View
29 Download

Altmetric

Share

Gmail Facebook X LinkedIn More