Robust Beamforming Design for IRS-Assisted Downlink Multi-User MISO-URLLC in an IIoT Scenario

Abstract

Intelligent reflecting surfaces (IRS) have recently been regarded as having potential for supporting multi-user (MU) multiple-input single-output (MISO) ultra-reliable and low-latency communication (URLLC) by creating favorable wireless communication links in the industrial IoT (IIoT) scenario. Hence, we studied the joint robust design of a beamformer at a central controller (CC) and phase shifters at the IRS for minimizing the transmit power consumption based on perfect channel state information (CSI) and imperfect CSI, respectively. The design was formulated as a non-convex optimization problem, also taking into account the quality-of-service (QoS) demands of the actuator, unit-modulus constraints of the IRS, and the robustness against the impact of CSI imperfection. Subsequently, we proposed a computationally efficient iterative algorithm to obtain a suboptimal solution by exploiting the penalty method and the successive convex approximation (SCA) for perfect CSI, while the penalty method, S-procedure, and SCA were adopted for imperfect CSI. Finally, our simulation results revealed that (1) the required transmit power consumption for URLLC was significantly reduced by employing the proposed IRS instead of conventional wireless communication without IRS; and (2) the proposed algorithm was robust and effective for the beamforming design.