Energy-Efficiency Optimization for RIS-Assisted UAV-Enabled IoT Networks

This paper studies the optimization of reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)-enabled Internet of Things (IoT) communication networks. In this framework, a rotary-wing UAV is dispatched to collect data form multiple ground IoT devices, leveraging the signal enhancement capabilities of an RIS to improve communication efficiency. We aim to enhance the overall energy efficiency (EE), taking into account both the system transmission rate and UAV propulsion power consumption, while satisfying the UAV initial/final position constraints, transmit power limits, and RIS unit-modules phase shift requirements. To achieve this goal, we first establish a closed-form analytical model for the EE of RIS-assisted UAV-enabled IoT wireless systems. Based on this model, we subsequently formulate the EE maximization (EEM) problem by jointly optimizing time allocation, transmit power control, RIS reflection coefficients, and UAV trajectory. Due to the non-convex nature of the proposed EEM problem, we decompose it into three subproblems: 1) RIS phase shift optimization with given resource allocation and UAV trajectory, 2) time and power allocation under fixed UAV trajectory and RIS configuration, and 3) UAV trajectory design based on provided resource allocation and RIS parameters. Particularly, the optimal phase shift solution is derived in a closed form to ensure phase alignment of signals from multiple transmission paths, while the non-convex resource allocation subproblem is solved through introducing relaxation variables. For UAV trajectory design, a hybrid optimization strategy combing Dinkelbach’s method and successive convex approximation approach is adopted to transform the non-convex EE optimization problem into a convex one. Numerical simulations demonstrate that the proposed EEM scheme obtains superior EE performance compared to benchmarks with fixed trajectory or without RIS deployment.