Joint Beamforming Design for IRS-Enabled DFRC Systems via Multiobjective Optimization

This paper considers jointly devising the transmit waveform, radar receive filters, passive reflection beamforming and communication equalizers for an intelligent reflecting surface (IRS)-aided dual-function radar and communication (DFRC) system in the existence of multiple radar targets and communication users. This scheme combines the design of the communication equalizers, along with the passive IRS beamforming. A general multiobjective optimization problem is addressed aiming at jointly optimizing the sensing and communication performance, while ensuring constant modulus plus similarity requirements on the transmit waveform, and the unit-modulus (UM) requirement of IRS weights. To tackle the constrained optimization problem, a low-complexity sequential optimization procedure is developed. In particular, at each iteration, the transmit waveform and the IRS beamforming are devised successively by the Riemannian conjugate gradient (RCG)-based approach, respectively. The asymptotic optimality and convergence of the proposed algorithm are studied. The effectiveness of the proposed algorithm is confirmed through representative numerical results.