Robust Weighted Sum Secrecy Rate Maximization for Joint ITS-and IRS-Assisted Multi-Antenna Networks

This letter investigates the robust beamforming design in a joint intelligent transmissive surface (ITS) and intelligent reflecting surface (IRS) aided secrecy multiuser multiple-input single-output (MISO) network under imperfect reflection channel state information (CSI). Specifically, the channel error of IRS-Bob and IRS-Eve links is assumed as norm-bounded and a weighted sum secrecy rate (WSSR) maximization problem is formulated under the constraints of transmit power budget of base station, ITS transmissive elements and unit modulus IRS phase shifts. To solve it, successive convex approximation (SCA), alternating optimization (AO) and Cauchy-Schwartz inequality are exploited, and a penalty method is applied to deal with the unit modulus constraints of IRS phase shifts. Numerical results validate the robustness of the proposed algorithm.