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

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

doi:10.1109/icassp49357.2023.10096832

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 proceeding › Conference contribution

12 Scopus citations

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 language	English (US)
Title of host publication	ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher	IEEE
DOIs	https://doi.org/10.1109/icassp49357.2023.10096832
State	Published - 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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10.1109/icassp49357.2023.10096832

Cite this

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title = "Compressive Estimation of Near Field Channels for Ultra Massive-Mimo Wideband THz Systems",

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.",

author = "Simon Tarboush and Anum Ali and Al-Naffouri, {Tareq Y.}",

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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language = "English (US)",

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T1 - Compressive Estimation of Near Field Channels for Ultra Massive-Mimo Wideband THz Systems

AU - Tarboush, Simon

AU - Ali, Anum

AU - Al-Naffouri, Tareq Y.

N1 - KAUST Repository Item: Exported on 2023-05-09 Acknowledgements: This work was supported by the KAUST Office of Sponsored Research.

PY - 2023/5/5

Y1 - 2023/5/5

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/691558

UR - https://ieeexplore.ieee.org/document/10096832/

U2 - 10.1109/icassp49357.2023.10096832

DO - 10.1109/icassp49357.2023.10096832

M3 - Conference contribution

BT - ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE

ER -

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

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