This paper addresses the mobility problem in massive multiple-input
multiple-output systems, which leads to significant performance losses in the
practical deployment of the fifth generation mobile communication networks. We
propose a novel channel prediction method based on multi-dimensional matrix
pencil (MDMP), which estimates the path parameters by exploiting the
angular-frequency-domain and angular-time-domain structures of the wideband
channel. The MDMP method also entails a novel path pairing scheme to pair the
delay and Doppler, based on the super-resolution property of the angle
estimation. Our method is able to deal with the realistic constraint of
time-varying path delays introduced by user movements, which has not been
considered so far in the literature. We prove theoretically that in the
scenario with time-varying path delays, the prediction error converges to zero
with the increasing number of the base station (BS) antennas, providing that
only two arbitrary channel samples are known. We also derive a lower-bound of
the number of the BS antennas to achieve a satisfactory performance. Simulation
results under the industrial channel model of 3GPP demonstrate that our
proposed MDMP method approaches the performance of the stationary scenario even
when the users' velocity reaches 120 km/h and the latency of the channel state
information is as large as 16 ms