  We consider the downlink of a MIMO-OFDM wireless systems where the
base-station (BS) has M antennas and serves K single-antenna user terminals
(UT) with K larger than or equal to M. Users estimate their channel vectors
from common downlink pilot symbols and feed back a prediction, which is used by
the BS to compute the linear beamforming matrix for the next time slot and to
select the users to be served according to the proportional fair scheduling
(PFS) algorithm. We consider a realistic physical channel model used as a
benchmark in standardization and some alternatives for the channel estimation
and prediction scheme. We show that a parametric method based on ESPRIT is able
to accurately predict the channel even for relatively high user mobility.
However, there exists a class of channels characterized by large Doppler spread
(high mobility) and clustered angular spread for which prediction is
intrinsically difficult and all considered methods fail. We propose a modified
PFS that take into account the "predictability" state of the UTs, and
significantly outperform the classical PFS in the presence of prediction
errors. The main conclusion of this work is that multiuser MIMO downlink yields
very good performance even in the presence of high mobility users, provided
that the nonpredictable users are handled appropriately
