Efficient Mirror Element Assignment in OIRS-Aided UAV-Based FSO Networks with Rate Adaptation

Optical intelligent reflective surfaces (OIRS) offer a promising solution for next-generation optical wireless communication (OWC) networks by mitigating the need for a line of sight (LoS) between ground stations and users. Unmanned aerial vehicles (UAVs) combined with OIRS can address non- availability of LoS links. This work proposes integrating an OWC-based network with an OIRS-aided UAV to support high data rates and broad coverage in next-generation communication networks. A key challenge is optimally assigning O IRS mirror elements to users to ensure their quality of service requirements. In this paper, we assign OIRS mirror elements to users to ensure that their rate demands are met. Specifically, we propose a channel quality-based mirror-element assignment (CMA) scheme to maximize the network sum-rate under hardware and rate demand constraints. Simulation results reveal that, compared to the traditional equal-mirror element assignment (EMA) scheme, CMA demonstrates superior performance in terms of sum-rate and coverage probability.