Hyemin Yu

Topic

Toward Intelligent Ubiquitous Connectivity: Trajectory Design and Resource Allocation for UAV-Enabled Wireless Networks

Department of Electrical and Computer Engineering

Date & location

• Wednesday, July 29, 2026

• 11:00 A.M.

• Virtual Defence

Reviewers

Supervisory Committee

• Dr. Hong-Chuan Yang, Department of Electrical and Computer Engineering, University of Victoria (Supervisor)

• Dr. Panajotis Agathoklis, Department of Electrical and Computer Engineering, UVic (Member)

• Dr. Jianping Pan, Department of Computer Science, UVic (Outside Member) 

External Examiner

• Dr. Patricia Basile, Department of Geography, Indiana University 

Chair of Oral Examination

• Dr. Mariko Sakamoto, School of Nursing, UVic 

Abstract

Uncrewed aerial vehicles (UAVs) are essential to realize ubiquitous broadband cover age due to their on-demand deployment, strong line-of-sight links, and controllable mobility. This thesis investigates trajectory design and communication resource allocation for UAV-enabled wireless networks to achieve ubiquitous connectivity. Specifically, two representative UAV roles are considered: UAVs as mobile relays and UAVs as aerial base stations (BSs). For UAV-assisted relaying, we study sustainable relay designs to extend connectivity in terrestrial and maritime environments. For UAV enabled aerial BSs, we study resource management solutions by satisfying average rate constraints and achieving max-min fairness under causal channel state information (CSI). Depending on the network architecture, operational constraints, and CSI availability, we develop optimization-based, reinforcement learning (RL)-based, and integrated optimization and RL-based solutions. First, a UAV-enabled terrestrial relay network is studied, where the UAV relay harvests energy and decodes information simultaneously to recharge the onboard battery and relay service time. To solve the aggregate throughput maximization problem, we develop an optimization-based solution using block coordinate descent and successive convex approximation. Second, a UAV-assisted maritime relay network is investigated to extend coverage over vast oceanic areas. We propose an RL-based solution to jointly design trajectory and link scheduling only using causal CSI, while guaranteeing on-time arrival at a final location. Third, reliable connectivity provision is studied for UAV-enabled wireless networks where the UAV serves as an aerial BS. Under the practical assumption that only causal CSI is available, we develop a constrained RL-based solution to jointly optimize UAV trajectory and transmit power, while satisfying average rate constraints. Finally, max-min fairness-oriented resource management is investigated to provide more balanced connectivity among users under causal CSI. As max-min fairness itself is an objective function as well as an optimization variable, we propose an integrated optimization and RL solution by combining the bisection method with RL to jointly optimize UAV trajectory and user scheduling. Simulation results show that the proposed solutions outperform benchmark schemes across different UAV-enabled network architectures.