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Details of Grant 

EPSRC Reference: EP/W004348/1
Title: Smart Solutions Towards Cellular-Connected Unmanned Aerial Vehicles System (AUTONOMY)
Principal Investigator: Deng, Dr Y
Other Investigators:
Aghvami, Professor AH Dohler, Professor M
Researcher Co-Investigators:
Project Partners:
AccelerComm Airborne Robotics Ericsson
Northrop Gruman (UK) Thales Ltd Toshiba
Department: Engineering
Organisation: Kings College London
Scheme: Standard Research
Starts: 01 April 2022 Ends: 31 March 2025 Value (£): 432,537
EPSRC Research Topic Classifications:
Artificial Intelligence Control Engineering
Networks & Distributed Systems RF & Microwave Technology
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Communications Information Technologies
Related Grants:
EP/W004364/1 EP/W004100/1
Panel History:
Panel DatePanel NameOutcome
21 Jun 2021 EPSRC ICT Prioritisation Panel 22-23 June 2021 Announced
Summary on Grant Application Form
The 5G-and-Beyond cellular networks promise UAVs with ultra-reliable low-latency control, ubiquitous coverage, and seamless swarm connectivity under complex and highly flexible multi-UAV behaviours in three-dimension (3D), which will unlock the full potential of UAVs. This so-called cellular-connected UAVs (C-UAVs) system creates a radically different and rapidly evolving networking and control environment compared to conventional terrestrial networks:

1) The UAV-ground BS/user channels enjoy fewer channel variations due to their dominant line-of-sight (LOS) characteristics, which imposes severe air-ground interference to the coexisting BSs/users in the uplink/downlink.

2) Operating in existing cellular networks designed mainly for dominate downlink traffic (e.g., video), the UAVs with high data rate requirement in uplink payload uploading, and ultra-reliable low-latency communication (URLLC) requirement in downlink command and control communication can hardly be satisfied.

3) Maintaining seamless connectivity for mission-centric UAV swarms with 3D high mobility is essential for UAV cooperation but extremely challenging.

4) Controlling a swarm of UAVs to accomplish complex tasks with limited human supervision under the connectivity constraints is of capital importance but challenging.

The above challenges can hardly be solved via conventional model-driven approaches, which are limited to performance evaluation or optimisation at one time instant in an offline or semi-offline manner, relying on given ideal probabilistic channel models without time correlation. Meanwhile, the future cellular networks in 5G-and-Beyond moves towards an open, programmable, and virtualised architecture with unprecedented data availability. Both facts mandate a fundamental change in the way we model, design, control, and optimise the C-UAVs system, from reactive/incident driven decoupled networking and control operation to proactive/ data-driven joint network and control design.

This project has the ambitious vision to develop artificial intelligence (AI)-powered C-UAVs system with full network automation and conditional control automation, that allow for joint design and optimization of the network operation and the UAVs control in real-time with minimum human supervision and the target of mission completion under the long-term quality of service (QoS) guarantees.

The project will engage with the end-users to exploit the C-UAVs applications in surveillance and emergency services in urban areas. Our results on network automation and control automation will directly benefit the telecom manufacturers (e.g., Ericsson AB, Toshiba Europe, AccelerComm), and broader UAV industries (e.g., Airborne Robotics, Thales, Northrop Grumman) internationally with foreseeable industrial impact. The NGMN and CommNet will facilitate the dissemination of the research outcomes nationally and internationally. The development, implementation, and testing of our proposed solutions serve as a platform towards the commercialisation of our research outcomes, putting the UK at the forefront of the "connected aerial vehicles" revolution.

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