A Survey of Wireless Networks for Future Aerial COMmunications (FACOM)
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Abstract (arXiv)
Electrification turned over a new leaf in aviation by introducing new types of aerial vehicles along with new means of transportation. Addressing a plethora of use cases, drones are gaining attention and increasingly appear in the sky. Emerging concepts of flying taxi enable passengers to be transported over several tens of kilometers. Therefore, unmanned traffic management systems are under development to cope with the complexity of future airspace, thereby resulting in unprecedented communication needs. Moreover, the increase in the number of commercial airplanes pushes the limits of voice-oriented communications, and future options such as single-pilot operations demand robust connectivity. In this survey, we provide a comprehensive review and vision for enabling the connectivity applications of aerial vehicles utilizing current and future communication technologies. We begin by categorizing the connectivity use cases per aerial vehicle and analyzing their connectivity requirements. By reviewing more than 500 related studies, we aim for a comprehensive approach to cover wireless communication technologies, and provide an overview of recent findings from the literature toward the possibilities and challenges of employing the wireless communication standards. After analyzing the network architectures, we list the open-source testbed platforms to facilitate future investigations. This study helped us observe that while numerous works focused on cellular technologies for aerial platforms, a single wireless technology is not sufficient to meet the stringent connectivity demands of the aerial use cases. We identified the need of further investigations on multi-technology network architectures to enable robust connectivity in the sky. Future works should consider suitable technology combinations to develop unified aerial networks that can meet the diverse quality of service demands.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Nov 2021.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 2.
4 papers.
- 2022UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithmscited by 3
- 2025Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approachescited by 2
- 2025Bridging Earth and Space: A Survey on HAPS for Non-Terrestrial Networkscited by 1
- 2024DeepAir: A Multi-Agent Deep Reinforcement Learning Based Scheme for an Unknown User Location Problemcited by 0
- 2025Bridging Earth and Space: A Survey on HAPS for Non-Terrestrial Networks22 Oct 2025
- 2025Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approaches19 Jul 2025
- 2024DeepAir: A Multi-Agent Deep Reinforcement Learning Based Scheme for an Unknown User Location Problem11 Aug 2024
- 2022UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms27 Nov 2022