  Mobility may degrade the performance of next-generation vehicular networks
operating at the millimeter-wave spectrum: frequent loss of alignment and
blockages require repeated beam training and handover, thus incurring huge
overhead. In this paper, an adaptive and joint design of beam training, data
transmission and handover is proposed, that exploits the mobility process of
mobile users and the dynamics of blockages to optimally trade-off throughput
and power consumption. At each time slot, the serving base station decides to
perform either beam training, data communication, or handover when blockage is
detected. The problem is cast as a partially observable Markov decision
process, and solved via an approximate dynamic programming algorithm based on
PERSEUS [2]. Numerical results show that the PERSEUS-based policy performs
near-optimally, and achieves a 55% gain in spectral efficiency compared to a
baseline scheme with periodic beam training. Inspired by its structure, an
adaptive heuristic policy is proposed with low computational complexity and
small performance degradation.
