# Intelligent Surface-Aided Transmitter Architectures for Millimeter Wave Ultra Massive MIMO Systems

## TL;DR

This paper proposes two innovative IRS/ITS-aided transmitter architectures for mmWave massive MIMO systems, leveraging passive reflecting surfaces to enhance energy efficiency and scalability while designing specialized precoders and analyzing power consumption.

## Contribution

It introduces novel IRS/ITS-aided architectures for mmWave MIMO, along with tailored precoder designs and a comprehensive power consumption model considering surface imperfections.

## Key findings

- IRS/ITS-aided architectures enable scalable, energy-efficient mmWave MIMO systems.
- Two precoder designs optimize mutual information and approximate fully digital precoding.
- Power consumption analysis accounts for practical IRS/ITS imperfections.

## Abstract

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.