Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted MIMO Systems in Vehicular Networks

Vehicle-to-Everything (V2X) is an important application scenario in 6G, where secure transmission is crucial in vehicular networks. Thus, this paper explores the application of an intelligent reflecting surface (IRS) in secure multipleinput multiple-output (MIMO) communication systems, which is subject to an eavesdropper equipped with multiple antennas. We formulate the secrecy rate maximization problem by jointly designing the transmit beamforming and the IRS phase-shift. Due to the coupling of the variables, the formulated problem is non-convex and thus we split the original problem into two sub-problems. For the two sub-problems, we first relax the sub-problem into a semi-definite program problem and solve it with the CVX tools. To further provide more insights into the calculation of the IRS phase-shift, we proposed the Riemannian manifold optimization (RMO) and majorization minimization (MM) algorithms to derive the closed-form solution of this subproblem. The numerical results validate that: 1) Through the proposed RMO and MM algorithms, the computation complexity is effectively reduced; and 2) the secure performance is significantly improved by the IRS.