Isac Beamforming Optimization For Robust Transmission In Dynamic Mmwave Mimo Networks

Acquiring accurate channel state information (CSI) is challenging in dynamic millimeter wave networks due to the excessive signaling overhead. In this work, we leverage the integrated sensing and communication (ISAC) technique for simultaneous data communication and CSI acquisition via proactive sensing. While offering a low overhead solution, ISAC beamforming design faces a complex trade-off between sensing accuracy and communication interference management. To handle it, we first formulate the ISAC beamforming design as an optimization problem that aims to minimize the worst sensing error subject to robust transmission rate constraints in the presence of CSI acquisition error. We then propose a benchmark algorithm by successive convex approximation. Further, we develop a low-complexity algorithm via dual optimization and max-min optimization methods. Simulation results demonstrate that the proposed design greatly outperforms existing schemes and achieves robust transmission in dynamic scenarios.