  This paper deals with the problem of localization in a cellular network in a
dense urban scenario. Global Navigation Satellite System typically performs
poorly in urban environments when there is no line-of-sight between the devices
and the satellites, and thus alternative localization methods are often
required. We present a simple yet effective method for localization based on
pathloss. In our approach, the user to be localized reports the received signal
strength from a set of base stations with known locations. For each base
station we have a good approximation of the pathloss at each location in the
map, provided by RadioUNet, an efficient deep learning-based simulator of
pathloss functions in urban environment, akin to ray-tracing. Using the
approximations of the pathloss functions of all base stations and the reported
signal strengths, we are able to extract a very accurate approximation of the
location of the user.
