  In this paper, the design of robust linear precoders for the massive
multi-input multi-output (MIMO) downlink with imperfect channel state
information (CSI) is investigated. The imperfect CSI for each UE obtained at
the BS is modeled as statistical CSI under a jointly correlated channel model
with both channel mean and channel variance information, which includes the
effects of channel estimation error, channel aging and spatial correlation. The
design objective is to maximize the expected weighted sum-rate. By combining
the minorize-maximize (MM) algorithm with the deterministic equivalent method,
an algorithm for robust linear precoder design is derived. The proposed
algorithm achieves a stationary point of the expected weighted sum-rate
maximization problem. To reduce the computational complexity, two
low-complexity algorithms are then derived. One for the general case, and the
other for the case when all the channel means are zeros. For the later case, it
is proved that the beam domain transmission is optimal, and thus the precoder
design reduces to the power allocation optimization in the beam domain.
Simulation results show that the proposed robust linear precoder designs apply
to various mobile scenarios and achieve high spectral efficiency.
