# Artificial Intelligence for UAV-enabled Wireless Networks: A Survey

arXiv: https://arxiv.org/abs/2009.11522 · HTML: https://mlsanity.com/paper/2009.11522/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2020.

## Built on by (most cited first, 11 of 11)

- [Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey](https://mlsanity.com/paper/2211.04324/) (2022)
- [Artificial Intelligence for Satellite Communication: A Review](https://mlsanity.com/paper/2101.10899/) (2021)
- [Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities](https://mlsanity.com/paper/2402.18062/) (2024)
- [Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control](https://mlsanity.com/paper/2210.00945/) (2022)
- [Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics](https://mlsanity.com/paper/2301.00912/) (2023)
- [Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems](https://mlsanity.com/paper/2302.04445/) (2023)
- [Joint Path planning and Power Allocation of a Cellular-Connected UAV using Apprenticeship Learning via Deep Inverse Reinforcement Learning](https://mlsanity.com/paper/2306.10071/) (2023)
- [Autonomous Advanced Aerial Mobility -- An End-to-end Autonomy Framework for UAVs and Beyond](https://mlsanity.com/paper/2311.04472/) (2023)
- [5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-based Integrated Access and Backhaul](https://mlsanity.com/paper/2202.02006/) (2022)
- [Bridging the Urban-Rural Connectivity Gap through Intelligent Space, Air, and Ground Networks](https://mlsanity.com/paper/2202.12683/) (2022)
- [Simulation-Based Study of AI-Assisted Channel Adaptation in UAV-Enabled Cellular Networks](https://mlsanity.com/paper/2602.13199/) (2026)

## Abstract (arXiv)

Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks. Their mobility and their ability to establish line of sight (LOS) links with the users made them key solutions for many potential applications. In the same vein, artificial intelligence (AI) is growing rapidly nowadays and has been very successful, particularly due to the massive amount of the available data. As a result, a significant part of the research community has started to integrate intelligence at the core of UAVs networks by applying AI algorithms in solving several problems in relation to drones. In this article, we provide a comprehensive overview of some potential applications of AI in UAV-based networks. We also highlight the limits of the existing works and outline some potential future applications of AI for UAV networks.