Enabling UAV cellular with millimeter-wave communication: potentials and approaches

By Zhenyu Xiao, Pengfei Xia, Xiang-Gen Xia. IEEE Communications Magazine, 2016

418 citations recorded by the source corpus.

To support high data rate urgent or ad hoc communications, we consider mmWave UAV cellular networks and the associated challenges and solutions. To enable fast beamforming training and tracking, we first investigate a hierarchical structure of beamforming codebooks and design of hierarchical codebooks with different beam widths via sub-array techniques. We next examine the Doppler effect as a result of UAV movement and find that the Doppler effect may not be catastrophic when high gain directional transmission is used. We further explore the use of mmWave spatial-division multiple access and demonstrate its clear advantage in improving the cellular network capacity. We also explore different ways of dealing with signal blockage and point out that possible adaptive UAV cruising algorithms would be necessary to counteract signal blockage. Finally, we identify a close relationship between UAV positioning and directional mmWave user discovery, where update of the former may directly impact the latter and vice versa.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/daccef36f6c09a8fde210116d2d26ee8cdc56f8c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Rui Zhang
2. Qingqing Wu
3. Yong Zeng
4. Shuowen Zhang
5. Robert Schober
6. Yuanwei Liu
7. Jie Xu
8. Naofal Al-Dhahir

In Electrical and Electronic Engineering

1. Rui Zhang
2. Qingqing Wu
3. Robert Schober
4. Yong Zeng
5. Shuowen Zhang
6. Yuanwei Liu
7. Naofal Al-Dhahir
8. Jie Xu

Citations in the corpus

• Multi-Agent Reinforcement Learning-Based Resource Allocation for UAV Networks (2018, background): “Aerial communication networks, encouraging new innovative functions to deploy wireless infrastructure, have recently attracted increasing interests for providing high network capacity and enhancing coverage [2], [3].”
• A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, methodology): “Besides, a fast beam searching algorithm was developed in [94] to track the UAV-to-ground channels based on a predetermined hierarchical codebook.”
• Cellular-Connected UAV: Potential, Challenges, and Promising Technologies (2018, background): “mIllImeter wAve cellulAr-connected uAvs MmWave communication that utilizes the wide available bandwidth above 28 GHz is a promising technology to achieve high-rate UAV communications [17].”
• A Survey of Channel Modeling for UAV Communications (2018, background): “The AA propagation channel is an important aspect of inter–UAV communications and can be exploited in applications, such as aerial wireless sensor networks [56], multi–UAV networks or UAV swarms [69], flying ad–hoc networks [76] and wireless back–haul connections using emerging technologies [77], [7”
• A Survey on Millimeter-Wave Beamforming Enabled UAV Communications and Networking (2021, background): “In addition to the above magazine papers [18], [21], [22], [32]–[34], a survey on 5G mmWave communications for UAV-assisted wireless networks was conducted in [8], where the authors reviewed the key technologies from seven different aspects, i.”
• Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, methodology): “The beam training with hierarchical beamforming codebooks has been shown to be an effective technique to achieve this goal [232], especially for LoS-dominant air-ground channels.”
• Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective (2018, methodology): “Finally, it is worth noting that UAV-assisted cellular communication can be integrated with other promising technologies for meeting the heterogeneous service demands in different application scenarios [83]–[94].”
• Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey (2021, background): “sent back to a control station for fast response [93] or in general to improve coverage for aerial vehicles by reducing the”