Statistical-QoS Guarantee for IoT Network Driven by Laser-Powered UAV Relay and RF Backscatter Communications

Abstract

Resource optimization is investigated for an unmanned aerial vehicle (UAV)-mounted relay assisted Internet-of-Things (U-IoT) network. A comprehensive network structure is proposed by incorporating laser-driven adaptive wireless-power-transfer at the UAV relay, wirelessly powered backscatter communication in the radio-frequency access links, and modulating retro-reflector based free space optical backhaul link in an optimization framework. Our objective is to maximize the number of the connected IoT devices with the UAV relay for uplink data transmission while satisfying the heterogeneous quality-of-service requirements of the IoT devices. Towards this objective, a novel optimization problem is formulated by considering queueing-overflow probability constraints of the IoT devices with stochastic data arrival, backhaul capacity constraint, and energy causality constraint at the UAV relay. The considered resource optimization is NP-hard, and an iterative solution is proposed by exploiting structure of the optimization problem. Furthermore, a three-stage optimization is devised to solve an NP-complete fractional optimization problem at each iteration of the proposed solution. An algorithm of polynomial computational complexity is developed for joint connectivity maximization and resource allocation, and convergence of the developed algorithm is proved. Using extensive simulations, efficiency of the proposed algorithm is demonstrated for improving the supportable arrival rate per IoT device and the number of the connected IoT devices in uplink of a U-IoT network.