Channel Estimation and Hybrid Combining for Wideband Terahertz Massive MIMO Systems

Abstract

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.

Efficient Channel Feedback Scheme for Multi-User MIMO Hybrid Beamforming Systems

“…To reflect the sparsity of the angle domain, the number of multi-path and scatterers are set to small numbers. The sparsity of the angle domain is shown in an environment that the number of propagation paths is close to one [ 3 , 28 ]. Furthermore, azimuth spread of departure (ASD), elevation spread of departure (ESD), azimuth spread of arrival (ASA), and elevation spread of arrival (ESA) are set to 3 degrees for the sparsity.…”

“…In the case of MIMO channel, the sparsity is also observed since the received signals of multiple antennas propagate through similar paths [ 3 ]. By exploiting the sparsity, compressed sensing (CS) can provide reasonable performance for channel estimation although the rate of antenna numbers is high [ 19 , 20 , 21 , 22 , 26 , 27 , 28 ]. The schemes can be classified into three groups.…”

“…The schemes of the first group have focused on the design of beam sweeping vectors to acquire qualified measurements for CS [ 19 , 26 ], and the schemes of the second group provided methods to reduce the computational load of the conventional OMP operation [ 21 , 22 , 26 , 28 ]. The schemes of the last group utilized structure of channel basis to improve the accuracy of channel estimation [ 20 , 27 , 28 ]. The topics are important subjects of CS-based channel estimation.…”

Hybrid Transceiver Design for Tera-Hertz MIMO Systems Relying on Bayesian Learning Aided Sparse Channel Estimation

“…where f i,g c0 and δ i,g denote the zero-pressure resonance frequency and linear pressure shift, respectively, which are also obtained from the HITRAN database. In (15), α air 0 and α i,g 0 represent the broadening coefficient of the air and of the ith isotopologue of the gth gas, respectively, whereas γ denotes the temperature broadening coefficient, all of which can be directly obtained from the HITRAN database, and the quantity T 0 denotes the reference temperature. The parameters involved in the calculation of molecular absorption coefficient k abs (f ), their units and the values of various constants are summarized in Table-I of [4].…”

“…Recent treatises, such as[14]-[16], address the problem of wideband CSI acquisition in THz systems. Specifically, Dovelos et al[15] consider an orthogonal frequency division multiplexing (OFDM)-based THz hybrid MIMO system and develop orthogonal matching pursuit (OMP)-based techniques for CSI estimation.Balevi and…”