  Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with
hybrid precoding is a promising technique for the future 5G wireless
communications. Due to a large number of antennas but a much smaller number of
radio frequency (RF) chains, estimating the high-dimensional mmWave massive
MIMO channel will bring the large pilot overhead. To overcome this challenge,
this paper proposes a super-resolution channel estimation scheme based on
two-dimensional (2D) u- nitary ESPRIT algorithm. By exploiting the angular
sparsity of mmWave channels, the continuously distributed angle of
arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy.
Specifically, by designing the uplink training signals at both base station
(BS) and mobile station (MS), we first use low pilot overhead to estimate a
low-dimensional effective channel, which has the same shift-invariance of array
response as the high-dimensional mmWave MIMO channel to be estimated. From the
low-dimensional effective channel, the super- resolution estimates of AoAs and
AoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channel
estimation algorithm. Furthermore, the associated path gains can be acquired
based on the least squares (LS) criterion. Finally, we can reconstruct the
high-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, and
path gains. Simulation results have confirmed that the proposed scheme is
superior to conventional schemes with a much lower pilot overhead.
