A Survey on Millimeter-Wave Beamforming Enabled UAV Communications and Networking
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Abstract (arXiv)
Unmanned aerial vehicles (UAVs) have found widespread commercial, civilian, and military applications. Wireless communication has always been one of the core technologies for UAV. However, the communication capacity is becoming a bottleneck for UAV to support more challenging application scenarios. The heavily-occupied sub-6 GHz frequency band is not sufficient to meet the ultra high-data-traffic requirements. The utilization of the millimeter-wave (mmWave) frequency bands is a promising direction for UAV communications, where large antenna arrays can be packed in a small area on the UAV to perform three-dimensional (3D) beamforming. On the other hand, UAVs serving as aerial access points or relays can significantly enhance the coverage and quality of service of the terrestrial mmWave cellular networks. In this paper, we provide a comprehensive survey on mmWave beamforming enabled UAV communications and networking. The technical potential of and challenges for mmWave-UAV communications are presented first. Then, we provide an overview on relevant mmWave antenna structures and channel modeling. Subsequently, the technologies and solutions for UAV-connected mmWave cellular networks and mmWave-UAV ad hoc networks are reviewed, respectively. Finally, we present open issues and promising directions for future research in mmWave beamforming enabled UAV communications and networking.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Apr 2021.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 2; 2026: 1.
5 papers.
- 2022Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSIcited by 6
- 2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Controlcited by 5
- 2025Resource-Efficient Beam Prediction in mmWave Communications with Multimodal Realistic Simulation Frameworkcited by 5
- 2025GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communicationcited by 0
- 2026Agentic AI for Embodied-enhanced Beam Prediction in Low-Altitude Economy Networkscited by 0
- 2026Agentic AI for Embodied-enhanced Beam Prediction in Low-Altitude Economy Networks12 Mar 2026
- 2025GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication23 May 2025
- 2025Resource-Efficient Beam Prediction in mmWave Communications with Multimodal Realistic Simulation Framework7 Apr 2025
- 2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control3 Oct 2022
- 2022Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI18 Jan 2022