  We consider a multiuser (MU) multiple-input multiple-output (MIMO)
time-division duplexing (TDD) system in which the base station (BS) is equipped
with a large number of antennas for communicating with single-antenna mobile
users. In such a system the BS has to estimate the channel state information
(CSI) that includes large-scale fading coefficients (LSFCs) and small-scale
fading coefficients (SSFCs) by uplink pilots. Although information about the
former FCs are indispensable in a MU-MIMO or distributed MIMO system, they are
usually ignored or assumed perfectly known when treating the MIMO CSI
estimation problem. We take advantage of the large spatial samples of a massive
MIMO BS to derive accurate LSFC estimates in the absence of SSFC information.
With estimated LSFCs, SSFCs are then obtained using a rank-reduced (RR) channel
model which in essence transforms the channel vector into a lower dimension
representation.
  We analyze the mean squared error (MSE) performance of the proposed composite
channel estimator and prove that the separable angle of arrival (AoA)
information provided by the RR model is beneficial for enhancing the
estimator's performance, especially when the angle spread of the uplink signal
is not too large.
