  Localization in outdoor wireless systems typically requires transmitting
specific reference signals to estimate distance (trilateration methods) or
angle (triangulation methods). These cause overhead on communication, need a
LoS link to work well, and require multiple base stations, often imposing
synchronization or specific hardware requirements. Fingerprinting has none of
these drawbacks, but building its database requires high human effort to
collect real-world measurements. For a long time, this issue limited the size
of databases and thus their performance. This work proposes significantly
reducing human effort in building fingerprinting databases by populating them
with \textit{digital twin RF maps}. These RF maps are built from ray-tracing
simulations on a digital replica of the environment across several frequency
bands and beamforming configurations. Online user fingerprints are then matched
against this spatial database. The approach was evaluated with practical
simulations using realistic propagation models and user measurements. Our
experiments show sub-meter localization errors on a NLoS location 95\% of the
time using sensible user measurement report sizes. Results highlight the
promising potential of the proposed digital twin approach for ubiquitous
wide-area 6G localization.
