Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Antenna Communications

Abstract

We investigate transmission optimization for intelligent reflecting surface (IRS) assisted multi-antenna systems from the physical-layer security perspective. The design goal is to maximize the system secrecy rate subject to the source transmit power constraint and the unit modulus constraints imposed on phase shifts at the IRS. To solve this complicated non-convex problem, we develop an efficient alternating algorithm where the solutions to the transmit covariance of the source and the phase shift matrix of the IRS are achieved in closed form and semi-closed forms, respectively. The convergence of the proposed algorithm is guaranteed theoretically. Simulations results validate the performance advantage of the proposed optimized design.

Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks

“…It is known that, both f A5 and f A6 are continuously differentiable functions, and the constraints in (16a) and (16b) are satisfied. Therefore, h A6 (ϕ,φ) is the SCA surrogate function of f A6 (ϕ), and we shall have the gradient of f A6 (ϕ): (11) and (12), and set t = 0. Repeat 3: Design κ using (21) according to ϕ (t) , α (t) , β (t) , W (t) ; 4: Set t = t + 1;…”

Secure MIMO Transmission via Intelligent Reflecting Surface

“…P2 is a complicated non-convex problem with both non-convex objective function and constraints, and the existing solutions (e.g., semi-definite relaxation and fractional programming) for IRS-assisted MISO case [2][3] cannot be directly applied to our problem. To optimize Q, we apply MM algorithm to solve P2, in which the key idea is to firstly obtain an approximately lower bound (i.e., surrogate function) of the objective, and then iteratively compute the optimal value of this bound subject to the constraints.…”

“…IRS is a low complexity software-controlled passive metasurface which could significantly help enhancing user's transmission rate with very low power consumption [1]. Motivated by these advantages, IRS was recently applied to the study in physical layer security, and several research results about secrecy rate maximization of IRS-assisted multiple-input multiple-output (MISO) wiretap channels wiretap channels were established, including single user case [2]- [4] and downlink multi-user case [5] [6]. All these studies indicate that IRS significantly enhance user's secrecy rate.…”

“…However, all the aformentioned contributions in the current literatures [2]- [6] are only restricted to MISO settings, i.e., only single antenna at the receiver as well as eavesdropper are considered. When multi-input multi-output (MIMO) is considered, there are two significant differences about the optimization problems compared with that in conventional MISO case.…”

“…In particular, the key difficulty is how to find a proper surrogate function for the complicated objective function. Hence, we apply three successive approximations for the objective function to obtain the proper lower bound so that MM alogrithm can be applied, which is significantly different from the existing MM used in the simple MISO case [2] [4] in which only one time approximation for the objective is needed due to the simple structure of the objective function. As the convergence is reached, the results returned by the AO algorithm is guaranteed to be a Karush-Khun-Tucker (KKT) solution of the original problem.…”