  A major source of difficulty when operating with large arrays at mmWave
frequencies is to estimate the wideband channel, since the use of hybrid
architectures acts as a compression stage for the received signal. Moreover,
the channel has to be tracked and the antenna arrays regularly reconfigured to
obtain appropriate beamforming gains when a mobile setting is considered. In
this paper, we focus on the problem of channel tracking for frequency-selective
mmWave channels, and propose two novel channel tracking algorithms that
leverage prior statistical information on the angles-of-arrival and
angles-of-departure. Exploiting this prior information, we also propose a
precoding and combining design method to increase the received SNR during
channel tracking, such that near-optimum data rates can be obtained with
low-overhead. In our numerical results, we analyze the performance of our
proposed algorithms for different system parameters. Simulation results show
that, using channel realizations extracted from the 5G New Radio channel model,
our proposed channel tracking framework is able to achieve near-optimum data
rates.
