Terahertz Sensing-assisted Mobile Communications: A Bayesian CRB-based Approach

The unprecedented surge in wireless data traffic has spurred extensive exploration in terahertz communications (THzComs) over the past decade. Since THzComs are vulnerable to performance degradation and even link outage in mobile scenarios, the integrated sensing and communications (ISAC) are expected to resolve the challenges by extracting information from received signals. Most existing efforts toward envisioned THz sensing-assisted mobile communication (TSAMC) technique merely take into account azimuth angle estimation according to sensing signals without angular velocity measurement, making their reliability and effectiveness questionable. To this end, this work provides a novel TSAMC approach to handle above challenges. Firstly, a four-dimensioned sensing containing amplitude measurement-based angular velocity estimation scheme is proposed to adjust practical high mobility scenarios. Secondly, a Bayesian Cramer-Rao bound (BCRB)-based information fusion ´ procedure is introduced to improve sensing accuracy by taking advantage of both sensing and communication echoes. Thirdly, estimated and integrated parameters are adopted for beam alignment, and the ergodic communication capacities in distinct cases of TSAMC are derived. Finally, the Monte Carlo simulation in mean squared error and achievable capacity, as well as performance bound evaluation in BCRB and capacity bound, are proceeded for sensing and communication individually. Numerical results verify the applicability of TSAMC framework, and validate the superiority of proposed method especially in high tangential mobility and communication-centric scenarios