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

Reliable Detection of Unknown Cell-Edge Users Via Canonical Correlation Analysis