Resource Allocation in a RIS-Assisted TDMA Wireless Powered Sensor Network Using UAV

Integrating reconfigurable intelligent surfaces (RISs) with energy harvesting technology offers a promising solution to enhance the performance of wireless networks. This letter investigates an RIS-assisted wireless powered sensor network (WPSN) where sensors distributed in an area harvest energy from an unmanned aerial vehicle (UAV) and subsequently transmit their data to the fusion center (FC) using the Time Division Multiple Access (TDMA) protocol, aided by an RIS mounted on the UAV. In the proposed model, the wireless power transfer (WPT) time is predetermined as a fraction of the total data transmission time and is excluded from the optimization variables. The objective is to maximize the sum throughput by optimally allocating time to the sensors and adjusting the phase shifts of the RIS elements. The resulting non-convex optimization problem is solved by decomposing it into two subproblems: first, determining the optimal phase shifts; and second, developing an algorithm for optimal time allocation using the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Excluding the WPT time from the optimization variables enables us to develop an efficient algorithm for time allocation with significantly reduced execution time compared to scenarios where WPT time is also an optimization variable, while maintaining comparable performance. Numerical results demonstrate that the proposed method significantly improves the network's performance.