A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems
Open accessAbstract
The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as 3D deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools, such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.
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Creation of channel models to represent A2G links is challenging as many factors need to be considered, such as UAV movement/vibration, altitude changes, type of UAV, propagation environment, antenna movements and shadowing.
“The creation of channel models to represent such A2G links is challenging as many factors need to be considered, such as a UAV's movement/vibration, changes in the UAVs altitude, type of UAV, type of propagation environment, antenna movements and shadowing caused by the UAVs own frame, to name a few [115].”
From A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022) · cites this paper as [115]
In probabilistic path-loss models, LoS and NLoS paths are considered separately with different occurrence probabilities determined by angle of elevation, building heights/densities and environment.
“Many works that adopt the probabilistic path-loss model consider LoS paths and NLos paths separately with different occurrence probabilities.These occurrence probabilities are determined by the angle of elevation between the UAV and ground device, building heights/densities and the environment itself [115].”
From A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022) · cites this paper as [115]
UAVs have been deployed for a diverse range of wireless communication purposes.
“UAVs (from small commercial drones to small aircrafts to balloons) have been able to be deployed for a diverse range of wireless communication purposes [115].”
From A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022) · cites this paper as [115]
Since wireless signal propagation is affected by the medium between a transmitter and receiver, this is problematic for UAV A2G communication.
“Since wireless signal propagation is affected by the medium between a transmitter and receiver, this is problematic for UAV A2G communication [115].”
From A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022) · cites this paper as [115]
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References 196 · Cited by 299
- Authors
- Mozaffari, M., Saad, W., Bennis, M., Nam, Y.-H., & Debbah, M.
- Affiliations
- Virginia Tech (US)
- University of Oulu (FI)
- Standards and 5G Mobility Innovations Laboratory, Samsung Research America, Richardson, TX, USA
- Mathematical and Algorithmic Sciences Laboratory, Huawei France Research and Development, Paris, France
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2019
- Volume
- 21
- Issue
- 3
- Pages
- 2334-2360
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2789361148
- Cited by
- 299
- References
- 196
- Citations by year
- 2026: 81 · 2025: 8 · 2024: 14 · 2023: 30 · 2022: 36 · 2021: 26 · 2020: 34 · 2019: 48 · 2018: 20 · 2017: 1
- FWCI
- 26.48
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, other-oa)
- arXiv (Cornell University)
- Funders
- Army Research Office (W911NF-17-1-0593)
- National Science Foundation (IIS-1633363)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Physical Sciences › Computer Science › Computer Networks and Communications › Mobile Ad Hoc Networks
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Keywords
- unmanned aerial vehicles, aerial base stations, channel modeling, energy efficiency, UAV communication, stochastic geometry, game theory, transport theory, optimization
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