  In this paper, a novel approach based on the concept of opportunistic spatial
orthogonalization (OSO) is proposed for interference management between machine
type communications (MTC) and conventional cellular communications. In
particular, a cellular system is considered with a multi-antenna BS in which a
receive beamformer is designed to maximize the rate of a cellular user, and, a
machine type aggregator (MTA) that receives data from a large set of MTDs. If
there is a large number of MTDs to choose from for transmission at each time
for each beamformer, one MTD can be selected such that it causes almost no
interference on the BS. A comprehensive analytical study of the characteristics
of such interference from several MTDs on the same beamformer is carried out.
It is proven that, for each beamformer, an MTD exists such that the
interference on the BS is negligible. However, the optimal implementation of
OSO requires the CSI of all the links in the BS, which is not practical for
MTC. To solve this problem, an online learning method based on the concept of
contextual multi-armed bandits (MAB) learning is proposed. Simulation results
show that is possible to implement OSO with no CSI from MTDs to the BS.
