Low-Latency Mobile Virtual Reality Content Delivery for Unmanned Aerial Vehicle-Enabled Wireless Networks With Energy Constraints

• Published in: IEEE transactions on vehicular technology Vol. 72; no. 2; pp. 2189 - 2201
• Main Authors: Dang, Tian, Liu, Chenxi, Peng, Mugen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Autonomous aerial vehicles; Complexity; Energy consumption; Energy storage; Iterative algorithms; Iterative methods; Kinematics; latency-energy trade-off; Low latency communication; Lyapunov optimization; Network latency; Optimization; Power control; resource allocation; Sensors; Trajectories; Trajectory; trajectory design; Unmanned aerial vehicle; Unmanned aerial vehicles; Virtual reality; virtual reality delivery; Wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3212868

In this paper, we leverage the benefits of unmanned aerial vehicle (UAV)-enabled wireless networks in providing high link qualities and on-demand services to achieve low-latency mobile virtual reality content delivery. Taking the limited energy storage at the UAVs into consideration, we formulate an average latency minimization problem, subject to the constraints on the UAV's kinematic, computation, and transmission capabilities. Utilizing the Lyapunov optimization approach, we first transform this NP-hard problem into a weighted-latency-plus-energy minimization problem for each time slot. Then, we further decompose the transformed problem into three subproblems, namely, the UAV's trajectory design subproblem, the UAV's processing frequency allocation subproblem, and the UAV's transmission power control subproblem. An iterative algorithm is proposed to solve these three subproblems. To reduce the complexity, we propose a low-complexity algorithm that designs the UAV's trajectory with the target of flight energy minimization. Through numerical results, we show that, compared to other benchmarks, our proposed algorithms can achieve a good trade-off between the average latency and the energy consumption by judiciously tuning the Lyapunov control parameter.