Fair Energy-Efficient Resource Optimization for Multi-UAV Enabled Internet of Things

• Published in: IEEE transactions on vehicular technology Vol. 72; no. 3; pp. 1 - 11
• Main Authors: Liu, Xin, Liu, Zechen, Lai, Biaojun, Peng, Bao, Durrani, Tariq S
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Autonomous aerial vehicles; Computational geometry; Convexity; Energy consumption; Energy efficiency; fairness; Flight time; Internet of Things; IoT; Optimization; Propulsion; Relays; resource optimization; Throughput; Trajectory; UAV; Unmanned aerial vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3219613

Unmanned aerial vehicle (UAV) enabled Internet of Things (IoT) can keep network connectivity when the ground infrastructures are paralyzed. However, its transmission perform will be restricted due to the limited energy of the UAV. In this paper, a multi-UAV enabled IoT is proposed, where the UAVs as base stations send information to the ground IoT nodes via downlink within the flight time. And a fair energy-efficient resource optimization scheme for the IoT is studied to ensure fair energy consumption of multiple UAVs. The optimization problem seeks to maximize the minimum energy efficiency of each UAV by jointly optimizing communication scheduling, power allocations and trajectories of the UAVs. We decompose the non-convex optimization problem into three sub-optimization problems and solve them by Dlinkelbach method and successive convex approximation (SCA). Then a joint optimization algorithm is put forward to obtain the global optimal solutions by iteratively optimizing the three sub-optimization problems. The simulations results show that the multi-UAV enabled IoT can achieve significant performance improvement, and the energy efficiency between UAVs can achieve relative fairness by the fair resource optimization.