Cost-efficient UAV placement and route planning for RIS-assisted communication networks

Abstract

In recent developments, reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for improving wireless signal propagation and extending coverage. Utilizing the mobility of unmanned aerial vehicles (UAVs), RIS-equipped UAVs (RIS-UAVs) can dynamically reposition themselves to function as aerial relays, facilitating line-of-sight (LoS) communication in environments obstructed by physical barriers. This paper aims to develop a cost-effective deployment and route-planning solution for RIS-UAVs. Most existing research on RIS-UAV placement and routing focuses on static RIS configurations or single UAV deployments, often neglecting critical real-world factors such as multiple geographically distributed hotspots, varying signal-to-noise ratio (SNR) requirements among users, UAV payload capacities, and energy constraints. To address these challenges, this paper decomposes the RIS-UAV placement and route planning problem into two NP-hard sub-problems, which are solved sequentially: (1) identifying optimal hover points and assigning RIS-UAVs to these locations; and (2) designing routes for each RIS-UAV that adhere to energy constraints. Simulation results show that the proposed approach can decrease the required number of RIS-UAVs by up to 53% compared to baseline methods using simulated annealing and artificial bee colony algorithms.