RIS-Assisted Energy-Efficient UAV Data Collection Method Based on Deep Reinforcement Learning
- 9 April 2025
- journal article
- research article
- Published by Springer Nature in Mobile Networks and Applications
- Vol. 30 (3-4) , 736-746
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (62173251)
- National Natural Science Foundation of China (62203113)
This publication has 23 references indexed in Scilit:
- UGV Charging Stations for UAV-Assisted AoI-Aware Data CollectionIEEE Transactions on Cognitive Communications and Networking, 2024
- Periodic Collaboration and Real-Time Dispatch Using an Actor–Critic Framework for UAV Movement in Mobile Edge ComputingIEEE Internet of Things Journal, 2024
- Reconfigurable UAV-aided 3D sustainable surveillance in classified air-spacesVehicular Communications, 2024
- Multi-UAV Assisted Network Coverage Optimization for Rescue Operations using Reinforcement Learning2023
- Joint Multi-UAV Path Planning and LoS Communication for Mobile-Edge Computing in IoT Networks With RISsIEEE Internet of Things Journal, 2022
- Energy-Efficient UAV-Mounted RIS Assisted Mobile Edge ComputingIEEE Wireless Communications Letters, 2022
- A Joint User Scheduling and Trajectory Planning Data Collection Strategy for the UAV-Assisted WSNIEEE Communications Letters, 2021
- 3D UAV Trajectory and Communication Design for Simultaneous Uplink and Downlink TransmissionIEEE Transactions on Communications, 2020
- A critical review on unmanned aerial vehicles power supply and energy management: Solutions, strategies, and prospectsApplied Energy, 2019
- UAV Communications for 5G and Beyond: Recent Advances and Future TrendsIEEE Internet of Things Journal, 2018