Abstract: Aiming at  the information security problems  caused by the broadcast characteristics in  wireless communications, we proposed a secrecy rate maximization algorithm based on alternating iteration. Firstly, considering non-ideal channel conditions, we modelled the secrecy rate maximization problem for an active reconfigurable intelligent surface (RIS)-assisted  multiple-input single-output (MISO) system with multiple eavesdroppers in the downlink. Secondly, aiming at the non-convexity and coupling of the optimization problem, we transformed the original non-convexity problem into two subproblems and  optimized  beamforming vector and the active RIS phase shift matrix of the base station separately. Finally, we used the alternating iteration and  the minimization-maximization (MM) algorithms  to transform the subproblems into convex optimization problems for solving. Simulation experiment results show  that compared with traditional schemes, the proposed algorithm improves the secrecy performance by 10%—35%, significantly enhances the system security performance and has  strong robustness, providing an effective and robust new method for solving wireless communication security problems in complex channel environments.

Key words: active reconfigurable intelligent surface, system secrecy rate, physical layer security, non-ideal channel state information, robust beamforming