  Efficient beam alignment is a crucial component in millimeter wave systems
with analog beamforming, especially in fast-changing vehicular settings. This
paper proposes a position-aided approach where the vehicle's position (e.g.,
available via GPS) is used to query the multipath fingerprint database, which
provides prior knowledge of potential pointing directions for reliable beam
alignment. The approach is the inverse of fingerprinting localization, where
the measured multipath signature is compared to the fingerprint database to
retrieve the most likely position. The power loss probability is introduced as
a metric to quantify misalignment accuracy and is used for optimizing candidate
beam selection. Two candidate beam selection methods are developed, where one
is a heuristic while the other minimizes the misalignment probability. The
proposed beam alignment is evaluated using realistic channels generated from a
commercial ray-tracing simulator. Using the generated channels, an extensive
investigation is provided, which includes the required measurement sample size
to build an effective fingerprint, the impact of measurement noise, the
sensitivity to changes in traffic density, and beam alignment overhead
comparison with IEEE 802.11ad as the baseline. Using the concept of beam
coherence time, which is the duration between two consecutive beam alignments,
and parameters of IEEE 802.11ad, the overhead is compared in the mobility
context. The results show that while the proposed approach provides increasing
rates with larger antenna arrays, IEEE 802.11ad has decreasing rates due to the
larger beam training overhead that eats up a large portion of the beam
coherence time, which becomes shorter with increasing mobility.
