A Robust Beamforming for Intergretd Sensing and Communications Systems

We propose a robust beamforming design methodology for integrated sensing and communications beamforms. The beamforming design aims to address channel uncertainties in the communication system by optimizing the sensing beamform. Assuming the Channel State Information (CSI) error is elliptically bounded, we investigate the robust integrated sensing and communication (ISAC) beamforming design problem, focusing on minimizing the Cramér-Rao bound (CRB) under a signal-to-noise ratio (SINR) threshold constraint. The problem is addressed through distributed optimization using the S-procedure and solved with the SDR method. Simulation results verify the effectiveness of the proposed CRB_min method.