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.

I. Introduction

Reconfigurable Intelligence Surface (RIS) is considered as a promising technology for future wireless communication systems due to their demonstrated capability to greatly enhance both spectral and energy efficiencies of network [1]. By controlling the microstructure of RIS units, their electromagnetic (EM) response can be altered, allowing precise regulation of the amplitude, phase, polarization, and frequency of incident EM waves. This enables accurate reflection or transmission of signals, allowing for active intervention in the propagation of wireless signals. Meanwhile, RIS is also used to form transmitters, and because it require much less radio frequency (RF) chain than antenna array, the power consumption of the RIS-based transmitter is greatly reduced [2]. Since the feed source of intelligent transmissive surface (ITS)-based transmitter does not obstruct signal transmission, it has higher aperture efficiency, larger working bandwidth, and less self-interference than intelligent reflective surface (IRS)-based transmitter [3].