Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System With Intelligent Reflecting Surface

In this letter, the achievable rate maximization problem is considered for intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems in an underlay spectrum sharing scenario, subject to interference power constraints at primary users. The formulated non-convex optimization challenging solve due its non-convexity as well coupling design variables constraints. Different from existing works that are mostly based on alternating (AO), we propose a penalty dual decomposition gradient projection (PDDGP) algorithm problem. We also provide convergence proof and complexity analysis proposed algorithm. benchmark against two known solutions, namely minimum mean-square error AO inner approximation method with block coordinate descent. Specifically, of grows linearly respect number elements IRS, while methods third IRS elements. Moreover, numerical results show PDDGP yields considerably higher than solutions.