UAV Communications Based on Non-Orthogonal Multiple Access
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Abstract (arXiv)
This article proposes a novel framework for unmaned aerial vehicle (UAV) networks with massive access capability supported by non-orthogonal multiple access (NOMA). In order to better understand NOMA enabled UAV networks, three case studies are carried out. We first provide performance evaluation of NOMA enabled UAV networks by adopting stochastic geometry to model the positions of UAVs and ground users. Then we investigate the joint trajectory design and power allocation for static NOMA users based on a simplified two-dimensional (2D) model that UAV is flying around at fixed height. As a further advance, we demonstrate the UAV placement issue with the aid of machine learning techniques when the ground users are roaming and the UAVs are capable of adjusting their positions in three-dimensions (3D) accordingly. With these case studies, we can comprehensively understand the UAV systems from fundamental theory to practical implementation.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Sep 2018.
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Citing papers per year: 2022: 3; 2023: 0; 2024: 1.
4 papers.
- 2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Controlcited by 26
- 2024Dynamic Trajectory and Power Control in Ultra-Dense UAV Networks: A Mean-Field Reinforcement Learning Approachcited by 2
- 2022Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehiclecited by 0
- 2022ProSky: NEAT Meets NOMA-mmWave in the Sky of 6Gcited by 0
- 2024Dynamic Trajectory and Power Control in Ultra-Dense UAV Networks: A Mean-Field Reinforcement Learning Approach21 Nov 2024
- 2022ProSky: NEAT Meets NOMA-mmWave in the Sky of 6G13 Oct 2022
- 2022Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehicle15 Feb 2022
- 2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control15 Jan 2022