Spectral Efficiency Optimization in IRS-Aided Multiuser MIMO SWIPT Cognitive Radio Systems

This paper considers the deployment of an intelligent reflecting surface (IRS) to assist a multiuser multiple-input multiple-output (MU-MIMO) simultaneous wireless information and power transfer (SWIPT) cognitive radio (CR) system. We aim to maximize the spectral efficiency (SE) of secondary users (SUs) subject to the power budget of the secondary base station (SBS), the minimum harvested energy requirement at each user, interference power of the primary users (PUs) by jointly optimizing transmit precoding (TPC) matrices at the SBS, the phase shift matrix at the IRS, and energy harvesting (EH) power-splitting (PS) factors at the users. By taking into account the non-linear EH models of the practical EH circuits at the users and the imperfect knowledge of the PU channel state information (CSI), the design problem is formulated as an intractable non-convex optimization problem. To efficiently deal with the non-convex problem in which the variables are coupled, we employ an alternating optimization to decouple the reformulated problem into three sub-problems by using the relationship between the data rate and the minimum mean-square error (MMSE). Then, we adopt the successive convex optimization to find lower bound concave functions for the non-linear EH ones and find the appropriate convex inner sets of the feasible sets to transform the optimization problems into convex ones. Finally, numerical results show that the deployment of the IRS can greatly enhance the achievable SE of SUs under both perfect and imperfect CSI cases.