Machine Learning Empowered Trajectory and Passive Beamforming Design in UAV-RIS Wireless Networks

@article{Liu2021MachineLE,
  title={Machine Learning Empowered Trajectory and Passive Beamforming Design in UAV-RIS Wireless Networks},
  author={Xiao Liu and Yuanwei Liu and Yue Chen},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2021},
  volume={39},
  pages={2042-2055}
}
A novel framework is proposed for integrating reconfigurable intelligent surfaces (RIS) in unmanned aerial vehicle (UAV) enabled wireless networks, where an RIS is deployed for enhancing the service quality of the UAV. Non-orthogonal multiple access (NOMA) technique is invoked to further improve the spectrum efficiency of the network, while mobile users (MUs) are considered as roaming continuously. The energy consumption minimizing problem is formulated by jointly designing the movement of the… 

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