RIS-Assisted UAV-Enabled Wireless Powered Communications: System Modeling and Optimization

IEEE Transactions on Wireless Communications(2023)

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摘要
This paper integrates a reconfigurable intelligent surface (RIS) and an unmanned aerial vehicle (UAV) into a wireless powered communication network. With the assistance of the RIS, multiple passive Internet of Things devices (IoTDs) gather energies from the signals of an energy station (ES) to power them to communicate with the UAV in time division multiple access mode. Given that the ES and the IoTDs are deployed by different service providers, an energy trading mechanism with price incentive is established through hierarchical Stackelberg game. By paying for the wireless charging service provided by the ES, the IoTDs aim to maximize the difference between achievable rate benefit and monetary payment, while the ES aims to maximize the difference between monetary payment and energy cost. To evaluate the impact of fairness, we propose sum-rate maximization (SRM) scheme and minimum-rate maximization (MRM) scheme, which take the sum-rate and minimum-rate of the IoTDs as achievable rate benefits, respectively. Specifically, in the follower game problem, an alternating optimization algorithm with majorization-minimization is utilized to alternately optimize energy beamforming and energy phase shifts (PSs) before optimal ES transmit power is achieved in closed form. In the leader game problem, a block coordinate descent algorithm with successive convex approximation is utilized to alternately optimize energy price, time allocation, and UAV trajectory after information PSs and transmit power of the IoTDs are achieved in closed form. Numerical results show that the combination of RIS and UAV significantly enhances the IoTD utility. Compared with the MRM scheme, the SRM scheme obtains higher IoTD utility at the cost of rate fairness and energy consumption.
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关键词
Game theory,wireless powered communication network,reconfigurable intelligent surface (RIS),unmanned aerial vehicle (UAV),trajectory optimization,energy trading,fairness
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