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UAV for Wireless Power Transfer in IoT Networks: A GMDP approach

Titre	UAV for Wireless Power Transfer in IoT Networks: A GMDP approach
Publication Type	Conference Paper
Year of Publication	2020
Authors	Lhazmir, S, Oualhaj, OA, Kobbane, A, Amlioud, EM, Ben-Othman, J
Conference Name	IEEE International Conference on Communications
Mots-clés	Antennas, Approximation algorithms, Behavioral research, Decision making, Decision-making problem, Energy transfer, Graphic methods, Inductive power transmission, Internet of things, Markov Decision Processes, Markov processes, Mean field approximation, Packet Delivery, System behaviors, System state, Unmanned aerial vehicles (UAV), Wireless energy, Wireless power
Abstract	Unmanned aerial vehicles (UAVs) are a promising technology employed as moving aggregators and wireless power transmitters for IoT networks. In this paper, we consider an UAV-IoT wireless energy and data transmission system and the decision-making problem is investigated. We aim at optimizing the nodes' utilities by defining a good packet delivery and energy transfer policy according to the system state. We formulate the problem as a Markov Decision Process (MDP) to tackle the successive decision issues. As the MDP formalism achieves its limits when the neighbors' interactions are considered, we formulate the problem as a Graph-based MDP (GMDP). We then propose a Mean-Field Approximation (MFA) algorithm to find a solution. The simulation results show that our framework achieves a good analysis of the system behavior. © 2020 IEEE.
URL	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089418365&doi=10.1109%2fICC40277.2020.9148956&partnerID=40&md5=a3d1ed58b9a7436f2191be8372102f51
DOI	10.1109/ICC40277.2020.9148956