  The high path loss associated with millimeter wave (mmWave) frequency
communication can be compensated by large scale antenna arrays such as
multiple-input multiple-output (MIMO) systems. The hybrid beamforming
architecture which uses fewer radio frequency chains is implemented to reduce
power consumption and hardware complexity, while still supporting multi-stream
communication. We propose an efficient expectation-maximization (EM)-based
mmWave channel estimator for a lens-based hybrid MIMO system with low
resolution sampling at the receiver. The lens-based beamformer is investigated
to provide increased antenna gain and reduced implementation complexity as the
conventional beam selection network is excluded. Low resolution sampling at the
analog-to-digital converters is implemented for reduced power consumption. The
proposed solution with a robust maximum a posteriori estimator based on the EM
algorithm performs better than the conventional EM approach and minimum mean
square error baselines in medium to high signal-to-noise ratio regions.
