Secrecy Capacity Maximization for IRS-Assisted High-Speed Train Communications - Li, Cuiran; Luan, Jiahui; Zhang, Zepeng; Ai, Bo; Wu, Hao; Xie, Jianli (IEEE communications letters, 2025)
In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanism are utilized to characterize highly time-varying wireless channels. The secrecy capacity optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) matrix, and IRS phase shifts, subject to transmit power and unit modulus constraints. To solve the non-convex problem, it is transformed into convex optimization problem by using weighted minimum mean square error (WMMSE) algorithm, and an alternating optimization strategy with coupled variables is used to derive the optimal solution. Simulation results show that the optimization algorithm proposed in this letter converges quickly and achieves higher secrecy capacity.