Near-Field Terahertz Communications: Model-Based and Model-Free Channel Estimation
Ahmet M. Elbir, Wei Shi, Anastasios K. Papazafeiropoulos, Pandelis, Kourtessis, Symeon Chatzinotas

TL;DR
This paper develops both model-based and model-free channel estimation methods for wideband near-field THz communications, addressing beam-split effects and demonstrating improved performance over existing techniques.
Contribution
It introduces a NB-aware dictionary for OMP-based estimation and a federated learning approach for multi-user scenarios, advancing near-field THz channel estimation.
Findings
OMP with NB-aware dictionary effectively mitigates beam-split effects.
Federated learning reduces training overhead in multi-user THz systems.
Proposed methods outperform existing state-of-the-art techniques.
Abstract
Terahertz (THz) band is expected to be one of the key enabling technologies of the sixth generation (6G) wireless networks because of its abundant available bandwidth and very narrow beam width. Due to high frequency operations, electrically small array apertures are employed, and the signal wavefront becomes spherical in the near-field. Therefore, near-field signal model should be considered for channel acquisition in THz systems. Unlike prior works which mostly ignore the impact of near-field beam-split (NB) and consider either narrowband scenario or far-field models, this paper introduces both a model-based and a model-free techniques for wideband THz channel estimation in the presence of NB. The model-based approach is based on orthogonal matching pursuit (OMP) algorithm, for which we design an NB-aware dictionary. The key idea is to exploit the angular and range deviations due to…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Microwave Engineering and Waveguides · Terahertz technology and applications
