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.

中文翻译：

---

即将卸任的主编致辞


V2X（Vehicle-to-Everything）是6G的重要应用场景，安全传输对于车载网络至关重要。因此，本文探讨了智能反射面（IRS）在安全多输入多输出（MIMO）通信系统中的应用，该系统会受到配备多个天线的窃听者的攻击。我们通过联合设计发射波束成形和 IRS 相移来制定保密率最大化问题。由于变量的耦合，公式化的问题是非凸的，因此我们将原始问题分成两个子问题。对于这两个子问题，我们首先将子问题放松为半定程序问题，并使用CVX工具对其进行求解。为了进一步深入了解 IRS 相移的计算，我们提出了黎曼流形优化 (RMO) 和主化最小化 (MM) 算法来推导该子问题的封闭式解。数值结果验证了：1）通过所提出的RMO和MM算法，有效降低了计算复杂度； 2) IRS 显着提高了安全性能。