Resource Allocation for an IRS-Assisted Dual-Functional Radar and Communication System: Energy Efficiency Maximization

Dual-functional radar and communication (DFRC) techniques are promising in the next generation wireless communication network. An intelligent reflecting surface (IRS) can improve the energy efficiency (EE) of the DFRC system, which is of crucial importance in practical applications. However, the EE achieved by using the sum-rate can be limited by the channel conditions and the radar performance requirement. Thus, in this paper, the EE maximization problem is studied in an IRS-assisted DFRC system. The EE is maximized by jointly optimizing the transmit beamforming and the IRS phase shift matrix under both the perfect channel state information (CSI) and the imperfect CSI cases. To tackle the challenging nonconvex fractional optimization problem, an alternating optimization algorithm is proposed. The high-order challenging radar performance constraint is tackled by using properties of the convex function and Hermitian matrix involved in the analysis. In the imperfect CSI case, the
${\mathcal{S}}$
-Procedure is applied to tackle the semi-infinite inequality arising from the channel uncertainty. Simulation results demonstrate that our proposed design enjoys fast convergence and achieves a higher EE compared to the benchmark schemes, even under imperfect CSI case. Furthermore, simulation results demonstrate that the EE of the DFRC system can be significantly improved by applying IRS.