  Millimeter Waves (mmWave) systems have the potential of enabling
multi-gigabit-per-second communications in future Intelligent Transportation
Systems (ITSs). Unfortunately, because of the increased vehicular mobility,
they require frequent antenna beam realignments - thus significantly increasing
the in-band Beamforming (BF) overhead. In this paper, we propose Smart
Motion-prediction Beam Alignment (SAMBA), a MAC-layer algorithm that exploits
the information broadcast via DSRC beacons by all vehicles. Based on this
information, overhead-free BF is achieved by estimating the position of the
vehicle and predicting its motion. Moreover, adapting the beamwidth with
respect to the estimated position can further enhance the performance. Our
investigation shows that SAMBA outperforms the IEEE 802.11ad BF strategy,
increasing the data rate by more than twice for sparse vehicle density while
enhancing the network throughput proportionally to the number of vehicles.
Furthermore, SAMBA was proven to be more efficient compared to legacy BF
algorithm under highly dynamic vehicular environments and hence, a viable
solution for future ITS services.
