  Providing reliable service to users close to the edge between cells remains a
challenge in cellular systems, even as 5G deployment is around the corner.
These users are subject to significant signal attenuation, which also degrades
their uplink channel estimates. Even joint detection using base station (BS)
cooperation often fails to reliably detect such users, due to near-far power
imbalance, and channel estimation errors. Is it possible to bypass the channel
estimation stage and design a detector that can reliably detect cell-edge user
signals under significant near-far imbalance? This paper shows, perhaps
surprisingly, that the answer is affirmative -- albeit not via traditional
multiuser detection. Exploiting that cell-edge user signals are weak but {\em
common} to different base stations, while cell-center users are unique to their
serving BS, this paper establishes an elegant connection between cell-edge user
detection and canonical correlation analysis (CCA) of the associated space-time
baseband-equivalent matrices. It proves that CCA identifies the common subspace
of these matrices, even under significant intra- and inter-cell interference.
The resulting mixture of cell-edge user signals can subsequently be unraveled
using a well-known algebraic signal processing technique. Interestingly, the
proposed approach does not even require that the signals from the different
base stations are synchronized -- the right synchronization can be
automatically determined as well. Experimental results demonstrate that the
proposed approach achieves order of magnitude BER improvements compared to
`oracle' multiuser detection that assumes perfect knowledge of the cell-center
user channels.
