  In this paper, we study two novel massive multiple-input multiple-output
(MIMO) transmitter architectures for millimeter wave (mmWave) communications
which comprise few active antennas, each equipped with a dedicated radio
frequency (RF) chain, that illuminate a nearby large intelligent
reflecting/transmitting surface (IRS/ITS). The IRS (ITS) consists of a large
number of low-cost and energy-efficient passive antenna elements which are able
to reflect (transmit) a phase-shifted version of the incident electromagnetic
field. Similar to lens array (LA) antennas, IRS/ITS-aided antenna architectures
are energy efficient due to the almost lossless over-the-air connection between
the active antennas and the intelligent surface. However, unlike for LA
antennas, for which the number of active antennas has to linearly grow with the
number of passive elements (i.e., the lens aperture) due to the
non-reconfigurablility (i.e., non-intelligence) of the lens, for IRS/ITS-aided
antennas, the reconfigurablility of the IRS/ITS facilitates scaling up the
number of radiating passive elements without increasing the number of costly
and bulky active antennas. We show that the constraints that the precoders for
IRS/ITS-aided antennas have to meet differ from those of conventional MIMO
architectures. Taking these constraints into account and exploiting the
sparsity of mmWave channels, we design two efficient precoders; one based on
maximizing the mutual information and one based on approximating the optimal
unconstrained fully digital (FD) precoder via the orthogonal matching pursuit
algorithm. Furthermore, we develop a power consumption model for IRS/ITS-aided
antennas that takes into account the impacts of the IRS/ITS imperfections,
namely the spillover loss, taper loss, aperture loss, and phase shifter loss.
