Terahertz (THz) communication is widely considered as a key enabler for future 6G wireless systems. However, THz links are subject to high propagation losses and intersymbol interference due to the frequency selectivity of the channel. Massive multiple-input multiple-output (MIMO) along with orthogonal frequency division multiplexing (OFDM) can be used to deal with these problems. Nevertheless, when the propagation delay across the base station (BS) antenna array exceeds the symbol period, the spatial response of the BS array varies over the OFDM subcarriers. This phenomenon, known as beam squint, renders narrowband combining approaches ineffective. Additionally, channel estimation becomes challenging in the absence of combining gain during the training stage. In this work, we address the channel estimation and hybrid combining problems in wideband THz massive MIMO with uniform planar arrays. Specifically, we first introduce a low-complexity beam squint mitigation scheme based on true-time-delay. Next, we propose a novel variant of the popular orthogonal matching pursuit (OMP) algorithm to accurately estimate the channel with low training overhead. Our channel estimation and hybrid combining schemes are analyzed both theoretically and numerically. Moreover, the proposed schemes are extended to the multiantenna user case. Simulation results are provided showcasing the performance gains offered by our design compared to standard narrowband combining and OMP-based channel estimation.

An intelligent reflecting surface (IRS) at terahertz (THz) bands is expected to have a massive number of reflecting elements to compensate for the severe propagation losses. However, as the IRS size grows, the conventional far-field assumption starts becoming invalid and the spherical wavefront of the radiated waves should be taken into account. In this work, we consider a spherical wave channel model and pursue a comprehensive study of IRS-aided multiple-input multiple-output (MIMO) in terms of power gain and energy efficiency (EE). Specifically, we first analyze the power gain under beamfocusing and beamforming, and show that the latter is suboptimal even for multiple meters away from the IRS. To this end, we derive an approximate, yet accurate, closed-form expression for the loss in the power gain under beamforming. Building on the derived model, we next show that an IRS can significantly improve the EE of MIMO when it operates in the radiating near-field and performs beamfocusing. Numerical results corroborate our analysis and provide novel insights into the design and performance of IRSassisted THz communication.

We study the uplink performance of massive multiple-input multiple-output (MIMO) when users are equipped with multiple antennas. To this end, we consider a generalized channel model that accounts for line-of-sight propagation and spatially correlated multipath fading. Most importantly, we employ the Weichselberger correlation model, which has been shown to alleviate the deficiencies of the popular Kronecker model. The main contribution of this paper is a rigorous closed-form expression for the uplink spectral efficiency using maximum-ratio combining and minimum mean square error channel estimation. Our result is a non-trivial generalization of previous results on massive MIMO with spatially correlated channels, thereby enabling us to have suitable designs for future massive MIMO systems. Numerical simulations corroborate our analysis and provide useful insights on how different propagation conditions affect system performance.

Multiple connected devices sharing common wireless resources might create interference if they access the channel simultaneously. Medium access control (MAC) protocols generally regulate the access of the devices to the shared channel to limit signal interference. In particular, irregular repetition slotted ALOHA (IRSA) techniques can achieve high-throughput performance when interference cancellation methods are adopted to recover from collisions. In this work, we study the finite length performance for IRSA schemes by building on the analogy between successive interference cancellation and iterative belief-propagation on erasure channels. We use a novel combinatorial derivation based on the matrix-occupancy theory to compute the error probability and we validate our method with simulation results.

Intelligent reflecting surface (IRS)-assisted wireless communication is widely deemed a key technology for 6G systems. The main challenge in deploying an IRS-aided terahertz (THz) link, though, is the severe propagation losses at high frequency bands. Hence, a THz IRS is expected to consist of a massive number of reflecting elements to compensate for those losses. However, as the IRS size grows, the conventional far-field assumption starts becoming invalid and the spherical wavefront of the radiated waves must be taken into account. In this work, we focus on the near-field and analytically determine the IRS response in the Fresnel zone by leveraging electromagnetic theory. Specifically, we derive a novel expression for the path loss and beampattern of a holographic IRS, which is then used to model its discrete counterpart. Our analysis sheds light on the modeling aspects and beamfocusing capabilities of THz IRSs.