Artificial Intelligence Aided Next-Generation Networks Relying on UAVs
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Abstract (arXiv)
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments. In the AI-enabled UAV-aided wireless networks (UAWN), multiple UAVs are employed as aerial base stations, which are capable of rapidly adapting to the dynamic environment by collecting information about the users' position and tele-traffic demands, learning from the environment and acting upon the feedback received from the users. Moreover, AI enables the interaction amongst a swarm of UAVs for cooperative optimization of the system. As a benefit of the AI framework, several challenges of conventional UAWN may be circumvented, leading to enhanced network performance, improved reliability and agile adaptivity. As a further benefit, dynamic trajectory design and resource allocation are demonstrated. Finally, potential research challenges and opportunities are discussed.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jan 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 2.
5 papers.
- 2022Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Surveycited by 27
- 2025UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVscited by 13
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challengescited by 12
- 2023A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challengescited by 1
- 2025Integrated Communication and Control for Energy-Efficient UAV Swarms: A Multi-Agent Reinforcement Learning Approachcited by 0
- 2025Integrated Communication and Control for Energy-Efficient UAV Swarms: A Multi-Agent Reinforcement Learning Approach28 Sep 2025
- 2025UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs8 Jun 2025
- 2023A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges25 Oct 2023
- 2022Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey7 Nov 2022
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges14 Nov 2021