  We investigate sensing-assisted predictive beamforming schemes for
vehicle-to-infrastructure (V2I) communication by exploiting the integrated
sensing and communication (ISAC) functionalities at the roadside unit (RSU).
The RSU deploys a massive multi-input-multi-output (mMIMO) array and operates
at millimeter wave (mmWave) frequencies. The pencil-sharp mMIMO beams and fine
range resolution achieved at mmWave, implicates that the point target
assumption is impractical in such V2I networks, as the volume and shape of the
vehicles become essential for beamforming. Simply pointing a beam to the
vehicle may result in the communication receiver (CR) never lying in the beam,
even when the vehicle's trajectory is accurately tracked. To tackle this
problem, we consider the extended vehicle target with two novel beam tracking
schemes. For the first scheme, the beamwidth is adjusted in real-time to cover
the entire vehicle, followed by an extended Kalman filtering (EKF) algorithm to
predict and track the position of CR according to the resolved high-resolution
scatterers. An upgraded scheme is further proposed by splitting each
transmission block into two stages. The first stage is exploited for ISAC
transmission, where a wide beam is adopted for both communication and sensing.
Based on the sensed results at the first stage, the second stage is dedicated
to communication by adopting a pencil-sharp beam, yielding a significant
improvement of the achievable rate. We further reveal the inherent tradeoff
between the two stages in terms of their durations, and develop an optimal time
allocation strategy that maximizes the average achievable rate. Finally,
numerical results are provided to verify the superiorities of proposed schemes
over the state-of-the-art methods.
