Abstract

This paper investigates a reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)-enabled wireless sensor network (WSN) under the probabilistic line-of-sight (LoS) channel in urban areas, where a UAV is dispatched to collect data from spatially distributed sensor nodes (SNs) with the aid of an RIS to enhance the communication quality. With the objective of maximizing the minimum average data collection rate from all the SNs for the UAV, we jointly design the communication scheduling, the phase shift of the RIS, and the UAV trajectory. However, due to its non-convexity, the formulated problem is difficult to solve. Therefore, we propose an efficient algorithm to attain its suboptimal solution by leveraging alternating optimization (AO), successive convex approximation (SCA), and semidefinite relaxation (SDR). Simulation results reveal new insights on the elevation angle-distance trade-off for the RIS-assisted UAV-enabled WSN, and the data collection rate of our proposed algorithm is significantly improved compared with other benchmark schemes.

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