In this paper, we study the problem of extremely large (XL) multiple-input multiple-output (MIMO) channel estimation in the Terahertz (THz) frequency band, considering the presence of propagation delays across the entire array apertures, which leads to frequency selectivity, a problem known as beam squint. Multi-carrier transmission schemes which are usually deployed to address this problem, suffer from high peak-to-average power ratio, which is specifically dominant in THz communications where low transmit power is realized. Diverging from the usual approach, we devise a novel channel estimation problem formulation in the time domain for single-carrier (SC) modulation, which favors transmissions in THz, and incorporate the beam-squint effect in a sparse vector recovery problem that is solved via sparse optimization tools. In particular, the beam squint and the sparse MIMO channel are jointly tracked by using an alternating minimization approach that decomposes the two estimation problems. The presented performance evaluation results validate that the proposed SC technique exhibits superior performance than the conventional one as well as than state-of-the-art multi-carrier approaches.

翻译：本文研究了太赫兹（THz）频段下极大规模（XL）多输入多输出（MIMO）信道估计问题，考虑整个阵列孔径上传播时延的存在所导致的频率选择性，即波束斜视效应。通常用于解决该问题的多载波传输方案具有高峰均功率比，而在太赫兹通信中此问题尤为突出，因为其发射功率较低。不同于常规方法，本文针对适用于太赫兹通信的单载波（SC）调制，提出了一种新颖的时域信道估计问题建模方法，并将波束斜视效应纳入稀疏向量恢复问题中，通过稀疏优化工具求解。具体而言，采用交替最小化方法将两个估计问题分解，从而联合追踪波束斜视和稀疏MIMO信道。性能评估结果验证了所提出的单载波技术优于传统方法及当前最优的多载波方案。