EKF-Based Beamforming Design for Joint Beam Tracking and Communication Systems

Beam tracking in the integrated sensing and communication (ISAC) system exhibits a unique challenge due to the tradeoff between sensing and communication subsystems. However, most existing research focuses on power allocation within specific systems but lacks a comprehensive beamforming design for standard joint beam tracking and communication systems. This letter proposes an extended Kalman filtering (EKF)-based beam tracking framework. Specifically, we develop a beamforming design method by formulating an optimization problem that minimizes the posterior Cramér-Rao bound (PCRB) within the EKF framework. Compared to existing approaches, the proposed method explicitly incorporates sensing channel information to enhance tracking accuracy. Numerical results show that the method improves sensing reliability, while quantitatively revealing the trade-off between tracking performance and communication rate.