This paper deals with the adoption of Unmanned Aerial Vehicles (UAVs) as mobile Base Stations providing video streaming services within a cellular macro area. We devise a Q-learning based UAV flight planning algorithm aimed at improving the Quality of Experience (QoE) of video users. Specifically, the proposed algorithm, herein denoted as Q-SQUARE, leverages the well-established Q-learning algorithm by introducing a reward related to a key QoE metric that is the video segment delay. The Q-SQUARE algorithm also accounts for different UAV recharging stations being available in the covered area. The performance analysis, as a function of the number of UAVs and recharging stations, show that Q-SQUARE identifies the UAV flight paths, i.e. specific space-time allocation of the available bandwidth resources, that definitely improve the QoE of the streaming services.

Colonnese, S., Cuomo, F., Pagliari, G., Chiaraviglio, L. (2019). Q-SQUARE: A Q-learning approach to provide a QoE aware UAV flight path in cellular networks. AD HOC NETWORKS, 91, 101872 [10.1016/j.adhoc.2019.101872].

Q-SQUARE: A Q-learning approach to provide a QoE aware UAV flight path in cellular networks

Chiaraviglio L.
2019-01-01

Abstract

This paper deals with the adoption of Unmanned Aerial Vehicles (UAVs) as mobile Base Stations providing video streaming services within a cellular macro area. We devise a Q-learning based UAV flight planning algorithm aimed at improving the Quality of Experience (QoE) of video users. Specifically, the proposed algorithm, herein denoted as Q-SQUARE, leverages the well-established Q-learning algorithm by introducing a reward related to a key QoE metric that is the video segment delay. The Q-SQUARE algorithm also accounts for different UAV recharging stations being available in the covered area. The performance analysis, as a function of the number of UAVs and recharging stations, show that Q-SQUARE identifies the UAV flight paths, i.e. specific space-time allocation of the available bandwidth resources, that definitely improve the QoE of the streaming services.
2019
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/03 - TELECOMUNICAZIONI
English
Con Impact Factor ISI
Cellular networks; Q-learning; Quality of experience; UAVs
Colonnese, S., Cuomo, F., Pagliari, G., Chiaraviglio, L. (2019). Q-SQUARE: A Q-learning approach to provide a QoE aware UAV flight path in cellular networks. AD HOC NETWORKS, 91, 101872 [10.1016/j.adhoc.2019.101872].
Colonnese, S; Cuomo, F; Pagliari, G; Chiaraviglio, L
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/242313
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