Seeing is Not Always Believing: ISAC-Assisted Predictive Beam Tracking
in Multipath Channels
Abstract
The integration of sensing and communications (ISAC) has brought
considerable benefit in predictive beamform?ing. However, it is
dedicated to the line-of-sight channels, and the effect of the spatial
degree of freedom (DoF) of multipath channels on ISAC performance has
not been revealed thus far. This compact letter proposed a novel
ISAC-assisted beam?tracking solution in multipath channels. Based on the
reflected echoes, the kinematic parameters are measured and the extended
Kalman filtering (EKF) is designed for angle prediction. The fine beam
tracking method is also proposed based on the tracking results of the
EKF. Simulation results show that the proposed method has a remarkable
superiority over the conventional feedback-based one. In addition, the
angle parameters observed from radar echoes are not always the optimal
alignment direction, which still has nearly a one-third gap from the
global optimal performance in a strong multipath environment, and this
gap can be bridged by the proposed fine beam tracking method.