# Resource Allocation for Secure IRS-assisted Multiuser MISO Systems

## TL;DR

This paper proposes a joint optimization framework for IRS-assisted multiuser MISO systems to enhance physical layer security by maximizing the sum secrecy rate through optimized phase shifts, beamforming, and artificial noise.

## Contribution

It introduces a novel joint optimization algorithm for IRS phase shifts, beamforming, and artificial noise in secure multiuser MISO systems, improving secrecy performance.

## Key findings

- Significant increase in sum secrecy rate compared to baseline schemes
- Efficient suboptimal algorithm effectively handles non-convex optimization
- Simulation results demonstrate the effectiveness of the proposed resource allocation

## Abstract

In this paper, we study resource allocation design for secure communication in intelligent reflecting surface (IRS)-assisted multiuser multiple-input single-output (MISO) communication systems. To enhance physical layer security, artificial noise (AN) is transmitted from the base station (BS) to deliberately impair the channel of an eavesdropper. In particular, we jointly optimize the phase shift matrix at the IRS and the beamforming vectors and AN covariance matrix at the BS for maximization of the system sum secrecy rate. To handle the resulting non-convex optimization problem, we develop an efficient suboptimal algorithm based on alternating optimization, successive convex approximation, semidefinite relaxation, and manifold optimization. Our simulation results reveal that the proposed scheme substantially improves the system sum secrecy rate compared to two baseline schemes.