  Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO)
systems realizing directive beamforming require reliable estimation of the
wireless propagation channel. However, mmWave channels are characterized by
high variability that severely challenges their recovery over short training
periods. Current channel estimation techniques exploit either the channel
sparsity in the beamspace domain or its low rank property in the antenna
domain, nevertheless, they still require large numbers of training symbols for
satisfactory performance. In this paper, we present a novel channel estimation
algorithm that jointly exploits the latter two properties of mmWave channels to
provide more accurate recovery, especially for shorter training intervals. The
proposed iterative algorithm is based on the Alternating Direction Method of
Multipliers (ADMM) and provides the global optimum solution to the considered
convex mmWave channel estimation problem with fast convergence properties.
