Compressive Estimation of Near Field Channels for Ultra Massive-Mimo Wideband THz Systems

Simon Tarboush, Anum Ali, Tareq Y. Al-Naffouri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we develop a channel estimation strategy for terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) system with a sub-connected array-of-subarrays architecture, in which one subarray (SA) is connected to one RF chain exclusively. Further, we consider a hybrid spherical-planar wave model (HSPM) for the channel modelling in which the channel between individual transmit and receive SAs is based on the planar wave model, while variation across the SAs is captured via the spherical wave model. Since the channel between different SAs is similar -albeit not identical - we propose a dictionary reduction based compressed sensing method to exploit the spatial information extracted from the estimates of the first SA in channel estimation of subsequent SAs. The proposed method achieves up to 2 dB NMSE improvement over the conventional methods.
Original languageEnglish (US)
Title of host publicationICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PublisherIEEE
DOIs
StatePublished - May 5 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-05-09
Acknowledgements: This work was supported by the KAUST Office of Sponsored Research.

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