  In a multiuser MIMO broadcast channel, the rate performance is affected by
the multiuser interference when the Channel State Information at the
Transmitter (CSIT) is imperfect. To tackle the detrimental effect of the
multiuser interference, a Rate-Splitting (RS) approach has been proposed
recently, which splits one selected user's message into a common and a private
part, and superimposes the common message on top of the private messages. The
common message is drawn from a public codebook and should be decoded by all
users. In this paper, we generalize the idea of RS into the large-scale array
regime with imperfect CSIT. By further exploiting the channel second-order
statistics, we propose a novel and general framework
Hierarchical-Rate-Splitting (HRS) that is particularly suited to massive MIMO
systems. HRS simultaneously transmits private messages intended to each user
and two kinds of common messages that can be decoded by all users and by a
subset of users, respectively. We analyse the asymptotic sum rate of RS and HRS
and optimize the precoders of the common messages. A closed-form power
allocation is derived which provides insights into the effects of system
parameters. Finally, simulation results validate the significant sum rate gain
of RS and HRS over various baselines.
