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UAV-assisted wireless charging and data processing of power IoT devices

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Abstract

To ensure the reliability and operational efficiency of the grid system, this paper proposes an unmanned aerial vehicle (UAV)-assisted Power Internet of Things (PIoT), which obtains real-time grid data through PIoT devices to support the management optimization of the grid system. Compared with traditional UAV-assisted communication networks, this paper enables data collection and energy transmission services for PIoT devices through UAVs. Firstly, the flight-hover-communication protocol is used. When the UAVs approach the target devices, they stop flying and remain hovering to provide services. The UAV selects full duplex mode in the hovering state, i.e., within the coverage area of the UAV, it can collect data from the target device while providing charging for other devices. Secondly, the UAVs can provide services to the required devices in sequence. Considering the priorities of the devices, both the data queue state and the energy pair state of network devices are considered comprehensively. Therefore, the optimization problem is constructed as a multi-objective optimization problem. First, the multi-objective optimization problem is transformed into a Markov process. Then, a multi-objective dynamic resource allocation algorithm based on reinforcement learning is proposed for solving the multi-objective optimization problem. The simulation results show that the proposed resource allocation scheme can effectively achieve a reasonable allocation of UAV resources, joint multi-objective optimization, and improved system performance.

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All data generated or analyzed during this study are included in this manuscript. Code may be available from the corresponding author on request.

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TL, JA, and HX wrote the main manuscript text, ML and FL prepared figures and tables. All authors reviewed the manuscript.

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Correspondence to Jianwei An or Haitao Xu.

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Lyu, T., An, J., Li, M. et al. UAV-assisted wireless charging and data processing of power IoT devices. Computing 106, 789–819 (2024). https://doi.org/10.1007/s00607-023-01245-y

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