Joint Resource Optimization for UAV-Enabled Multichannel Internet of Things Based on Intelligent Fog Computing

• Published in: IEEE transactions on network science and engineering Vol. 8; no. 4; pp. 2814 - 2824
• Main Authors: Liu, Xin, Lai, Biaojun, Gou, Linfeng, Lin, Chuan, Zhou, Mu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Base stations; Cloud computing; Data centers; Edge computing; fairness optimization; Internet of Things; Iterative methods; joint resource optimization; multichannel IoT; Nodes; Optimization; Relays; Resource management; Subcarriers; Trajectory optimization; transmit rate; UAV relay; Unmanned aerial vehicles
• ISSN: 2327-4697; 2334-329X
• DOI: 10.1109/TNSE.2020.3027098

Due to flexible scheduling, and better transmission channel, unmanned aerial vehicle (UAV) can improve transmit performance of Internet of Things (IoT). In this paper, we propose an UAV-enabled multichannel IoT based on intelligent fog computing, where UAV as a relay forwards IoT's information to the data center under the control of fog computing base station in the case of terrestrial channel fading. The IoT's throughput are maximized by jointly optimizing subcarrier, power of IoT, and UAV, and UAV trajectory, subject to the constraints of information causality, maximum transmit power, and maximum UAV speed. The subcarriers are dynamically allocated according to their channel gains, the water filling algorithm is adopted to optimize the power for UAV, and IoT by fixing UAV trajectory, and the optimal UAV trajectory is achieved with successive convex approximation under the fixed power allocation. Then a jointly iterative optimization on subcarrier, power, and trajectory is presented to get the optimal solution. In addition, we propose a fairness optimization scheme to maximize the minimum transmit rate of IoT nodes. The simulations indicate the IoT with mobile UAV, and dynamic subcarrier allocation may achieve better transmit performance, and the fairness optimization can decrease the rate difference of nodes effectively.