Minimizing Ground Risk in Cellular-Connected Drone Corridors with mmWave Links

• Published in: IEEE transactions on aerospace and electronic systems Vol. 59; no. 6; pp. 1 - 16
• Main Authors: Singh, Simran, Sichitiu, Mihail L., Guvenc, Ismail, Bhuyan, Arupjyoti
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; A search; Algorithms; Autonomous aerial vehicles; beamforming; Cellular Drone; conflict-based search (CBS); Drone aircraft; Drone Corridor; Drones; GENERAL AND MISCELLANEOUS; ground risk; Heuristic methods; Internet of Things; Millimeter wave communication; Millimeter waves; mmWave; multi-agent path finding (MAPF); Performance evaluation; Ray tracing; Risk; Signal strength; Trajectories; Trajectory; Unmanned aerial vehicles; Unmanned aircraft; unmanned aircraft system (UAS); Urban environments; UTM; Wireless communication; Wireless communications
• ISSN: 0018-9251; 1557-9603; 2371-9877; 1557-9603
• DOI: 10.1109/TAES.2023.3301824

Unmanned aircraft systems (UAS) have been receiving significant interest and support from academia, industry, and regulatory bodies over the past decade due to their various use cases. To safely integrate UAS operations into the national airspace, particularly overpopulated regions, the risk posed to ground users, buildings, and vehicles due to unmanned aerial vehicle (UAV) flight should be minimized. This risk can be represented by a numerical metric, which we refer to in this paper as the "ground risk". Many UAS applications also depend on the presence of a reliable wireless communication link between the UAV and a control station for the transmission of UAV position, surveillance video, UAV payload commands, and other mission-related data. Such wireless communication requirements also need to be considered in the design of UAS operations. In this work, we consider both these aspects and study the design of non-intersecting trajectories for UAS operations to minimize ground risk, subject to constraints on the wireless signal strength and geometry of the trajectory, specified in terms of: i) an enclosing cylinder within which the trajectory must lie, and ii) an integrated angular change along the UAV's trajectory. The performance of a computationally expensive optimal algorithm is compared with a computationally faster heuristic approach within the dense urban environment of Manhattan, NY. Performance evaluation using ray tracing simulations shows that the heuristic approach performs close to the optimal algorithm at a reduced computation cost. This research can be utilized to make UAS operations safe and reliable, and accelerate their adoption.