Robust Beamforming for Intelligent Reflecting Surface Aided Dual-Functional Radar-Communication System

Intelligent reflecting surface (IRS) has recently gained significant academic interest as a prospective contender for improving wireless communication system coverage and spectral efficiency. This paper investigates a robust beamforming design of an IRS-aided dual-functional radar-communication (DFRC) system in the presence of channel uncertainty, as opposed to the idealistic assumption of perfect channel state information (CSI) in the existing literature. The optimization is carried out by minimizing the transmit power while ensuring the detection performance and the achievable rate of the user meets the quality of service (QoS) requirement, which turns out to be a non-convex and intractable problem. To circumvent this issue, we alternatively update the transmit beamforming vector and the phase shifts at the IRS using the block coordinate descent (BCD) algorithm. Afterwards, the resulting two sub-problems can be efficiently solved with the help of approximation and transformation techniques. Simulation results have validated the convergence and effectiveness of the proposed algorithm.