  Large-scale MIMO systems are well known for their advantages in
communications, but they also have the potential for providing very accurate
localization thanks to their high angular resolution. A difficult problem
arising indoors and outdoors is localizing users over multipath channels.
Localization based on angle of arrival (AOA) generally involves a two-step
procedure, where signals are first processed to obtain a user's AOA at
different base stations, followed by triangulation to determine the user's
position. In the presence of multipath, the performance of these methods is
greatly degraded due to the inability to correctly detect and/or estimate the
AOA of the line-of-sight (LOS) paths. To counter the limitations of this
two-step procedure which is inherently sub-optimal, we propose a direct
localization approach in which the position of a user is localized by jointly
processing the observations obtained at distributed massive MIMO base stations.
Our approach is based on a novel compressed sensing framework that exploits
channel properties to distinguish LOS from non-LOS signal paths, and leads to
improved performance results compared to previous existing methods.
