Joint Optimization of Semi-Passive IRS Phase Shifts and NOMA Power Coefficients for Cooperative CRNs

Abstract

We investigate the incorporation of an intelligent reflecting surface (IRS) into cooperative spectrum-sharing cognitive radio networks (CRNs). The CRN consists of a primary user (PU) and multiple secondary users (SUs). There are two transmission phases. In the first phase, the primary transmitter is assisted by an IRS to serve the primary user (PU). This arrangement allows the primary network to allocate a part of its spectrum to the users within the secondary network. In the subsequent phase, the secondary transmitter (ST) employs a non-orthogonal multiple access (NOMA) transmission technique to simultaneously serve the PU and secondary users (SUs). By utilizing a semi-passive IRS, both data transmission to the PU and channel estimation of SUs are performed simultaneously during the first transmission phase. The main objective is to improve the weighted sum-rate of the CRN through a joint optimization of the NOMA power coefficients and IRS phase adjustments during the second transmission phase. We propose an effective algorithm that breaks down the primary sum-rate maximization problem into two sub-problems where IRS phase shifts are computed once at the beginning of the algorithm. Through simulations, we demonstrate that the proposed algorithm yields substantial gains in the sum-rate performance compared to existing methods.