IRS-User Association in Multi-IRS Assisted Cognitive Radio Networks

In this paper, we consider multiple intelligent reflecting surfaces (IRSs) assisted cognitive radio network (CRN) and investigate user-IRS association problem. The CRN consists of multiple secondary transmitters (STs), multiple secondary users (SUs) and a single primary user (PU). With the help of IRSs, the received signal strength at the SUs is improved. This is achieved by optimizing IRS phase shifts, which also helps reducing the interference at the PU. The main objective of this study is to obtain the user-IRS association that maximizes the minimum rate of the user in the network. For this purpose, we employ the well-known optimal relay assignment (ORA) algorithm, known for its polynomial-time complexity. The numerical results clearly demonstrate that the user-IRS assignment obtained through the ORA algorithm yields higher minimum rate performance compared to the sum-rate maximizing and random user-IRS assignment methods.