Hybrid Beamforming Optimization for Mixed Far- and Near-Field ISAC Under Imperfect CSI

Abstract

Integrated sensing and communications (ISAC) has significantly improved resource efficiency through spectrum and hardware sharing, and has become a key enabling technology for the next generation of wireless networks. Meanwhile, the deployment of extremely large-scale antenna arrays (ELAAs) and high carrier frequencies inevitably transition the signal propagation environment into a complex mixed far-field and near-field regime. However, practical mixed-field ISAC systems face severe hardware constraints and inevitable channel state information (CSI) errors. To address these challenges, this letter investigates a robust hybrid beamforming design for mixed-field ISAC under imperfect CSI. We formulate a max-min communication rate optimization problem subject to stringent sensing requirements that jointly designs receive filters, analog and digital beamformers. To tackle the resulting highly non-convex problem, we propose an efficient double-loop penalty-based algorithm. Simulation results show that the proposed scheme is robust to CSI errors and achieves performance close to fully-digital beamforming. In addition, it satisfies the sensing requirement with negligible communication rate degradation and significantly outperforms conventional far-field designs.