Matching Theory-Based Resource Allocation and Spectrum Sharing for UAV-RIS Assisted Cellular-IoT Systems
Unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) are two emerging technologies envisioned for sixth-generation (6G) wireless systems. These technologies enhance conventional cellular networks by extending coverage and enabling ubiquitous connectivity. However, spectrum scarcity and interoperability challenges create a strong need for efficient spectrum sharing among cellular users supported by these technologies. In this context, this paper considers a dynamic spectrum-sharing method in which data rate-aware spectrum sharing plays a critical role in managing base station power consumption and mitigating interference. We investigate a UAV-RIS-assisted cellular system where legacy cellular users share the spectrum with cellular Internet-of-Things (IoT) devices. To enhance the overall system sum data rate, we propose a joint user pairing, spectrum, power allocation, and RIS phase shift optimization approach based on matching theory. Simulation results demonstrate the effectiveness of the proposed method in improving resource allocation efficiency and significantly enhancing the sum data rate performance of wireless communication systems.