THz-Band Near-Field RIS Channel Modeling for Linear Channel Estimation

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Dkhan, Ahmad, Tarboush, Simon, Sarieddeen, Hadi, Abou-Faycal, Ibrahim, Al-Naffouri, Tareq Y.
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866915287860772864
author Dkhan, Ahmad
Tarboush, Simon
Sarieddeen, Hadi
Abou-Faycal, Ibrahim
Al-Naffouri, Tareq Y.
author_facet Dkhan, Ahmad
Tarboush, Simon
Sarieddeen, Hadi
Abou-Faycal, Ibrahim
Al-Naffouri, Tareq Y.
contents Reconfigurable intelligent surface (RIS)-aided terahertz (THz)-band communications are promising enablers for future wireless networks. However, array densification at high frequencies introduces significant challenges in accurate channel modeling and estimation, particularly with THz-specific fading, mutual coupling (MC), spatial correlation, and near-field effects. In this work, we model THz outdoor small-scale fading channels using the mixture gamma (MG) distribution, considering absorption losses, spherical wave propagation, MC, and spatial correlation across large base stations and RISs. We derive the distribution of the cascaded RIS-aided channel and investigate linear channel estimation techniques, analyzing the impact of various channel parameters. Numerical results based on precise THz parameters reveal that accounting for spatial correlation, MC, and near-field modeling substantially enhances estimation accuracy, especially in ultra-massive arrays and short-range scenarios. These results underscore the importance of incorporating these effects for precise, physically consistent channel modeling.
format Preprint
id arxiv_https___arxiv_org_abs_2505_09767
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle THz-Band Near-Field RIS Channel Modeling for Linear Channel Estimation
Dkhan, Ahmad
Tarboush, Simon
Sarieddeen, Hadi
Abou-Faycal, Ibrahim
Al-Naffouri, Tareq Y.
Signal Processing
Reconfigurable intelligent surface (RIS)-aided terahertz (THz)-band communications are promising enablers for future wireless networks. However, array densification at high frequencies introduces significant challenges in accurate channel modeling and estimation, particularly with THz-specific fading, mutual coupling (MC), spatial correlation, and near-field effects. In this work, we model THz outdoor small-scale fading channels using the mixture gamma (MG) distribution, considering absorption losses, spherical wave propagation, MC, and spatial correlation across large base stations and RISs. We derive the distribution of the cascaded RIS-aided channel and investigate linear channel estimation techniques, analyzing the impact of various channel parameters. Numerical results based on precise THz parameters reveal that accounting for spatial correlation, MC, and near-field modeling substantially enhances estimation accuracy, especially in ultra-massive arrays and short-range scenarios. These results underscore the importance of incorporating these effects for precise, physically consistent channel modeling.
title THz-Band Near-Field RIS Channel Modeling for Linear Channel Estimation
topic Signal Processing
url https://arxiv.org/abs/2505.09767