An IRS-Assisted Secure Dual-Function Radar-Communication System

TL;DR

This paper introduces a novel IRS-assisted approach to enhance physical layer security in dual-function radar-communication systems by jointly optimizing waveform, artificial noise, and IRS parameters.

Contribution

It proposes a new optimization framework using fractional programming to improve secrecy rate while satisfying radar SNR constraints in DFRC systems.

Findings

The proposed algorithm converges effectively.

Artificial noise power significantly impacts secrecy performance.

IRS parameter optimization enhances security in DFRC systems.

Abstract

In dual-function radar-communication (DFRC) systems the probing signal contains information intended for the communication users, which makes that information vulnerable to eavesdropping by the targets. We propose a novel design for enhancing the physical layer security (PLS) of DFRC systems, via the help of intelligent reflecting surface (IRS) and artificial noise (AN), transmitted along with the probing waveform. The radar waveform, the AN jamming noise and the IRS parameters are designed to optimize the communication secrecy rate while meeting radar signal-to-noise ratio (SNR) constrains. Key challenges in the resulting optimization problem include the fractional form objective, the SNR being a quartic function of the IRS parameters, and the unit-modulus constraint of the IRS parameters. A fractional programming technique is used to transform the fractional form objective of the optimization problem into more tractable non-fractional polynomials. Numerical results are provided to demonstrate the convergence of the proposed system design algorithm, and also show the impact of the power assigned to the AN on the secrecy performance of the designed system.