Millimeter Wave MIMO Channel Estimation Using Sub-6 GHz Out-of-Band Information

Next-generation wireless communication systems will incorporate millimeter wave (mmWave) as one of the key technologies to increase data rates. These forthcoming mmWave systems will integrate multiple-input multiple-output (MIMO) technology to ensure sufficient link margin and are expected to be deployed in conjunction with sub-6 GHz systems. Configuring a MIMO communication link usually relies on estimating channel state information (CSI), which is difficult to acquire at mmWave frequencies due to the low pre-beamforming signal-to-noise ratio (SNR). In this paper, we propose a novel approach to estimate mmWave MIMO channels by leveraging out-of-band information from a sub-6GHz band. Utilizing this approach, we develop three channel estimation methods and compare these methods with one using only in-band information. We investigate the influence of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i>-factor, the SNR and the number of antennas on the performance of the proposed channel estimation methods through simulations. Additionally, we compare these methods in terms of their computational complexity. Finally, we validate the performance of the proposed methods through channel measurements conducted in an outdoor environment. The results demonstrate that the proposed methods outperform in-band mmWave channel estimation in terms of spectral efficiency, particularly in scenarios of low SNR and high K-factor.

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Publication Details

Journal
IEEE Transactions on Communications
Published
2025-07-14
DOI
https://doi.org/10.1109/tcomm.2025.3588591
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Millimeter Wave MIMO Channel Estimation Using Sub-6 GHz Out-of-Band Information

Mariam Mussbah, Markus Rupp, Christoph F. Mecklenbräuker, Sebastian Caban et al.
IEEE Transactions on Communications
Millimeter-Wave Propagation and Modeling
article

Millimeter Wave MIMO Channel Estimation Using Sub-6 GHz Out-of-Band Information

Mariam Mussbah, Markus Rupp, Christoph F. Mecklenbräuker, Sebastian Caban, Thomas Zemen, Markus Hofer, Seun Sangodoyin, Andreas F. Molisch, Faruk Pasic
article en

Abstract

Next-generation wireless communication systems will incorporate millimeter wave (mmWave) as one of the key technologies to increase data rates. These forthcoming mmWave systems will integrate multiple-input multiple-output (MIMO) technology to ensure sufficient link margin and are expected to be deployed in conjunction with sub-6 GHz systems. Configuring a MIMO communication link usually relies on estimating channel state information (CSI), which is difficult to acquire at mmWave frequencies due to the low pre-beamforming signal-to-noise ratio (SNR). In this paper, we propose a novel approach to estimate mmWave MIMO channels by leveraging out-of-band information from a sub-6GHz band. Utilizing this approach, we develop three channel estimation methods and compare these methods with one using only in-band information. We investigate the influence of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i>-factor, the SNR and the number of antennas on the performance of the proposed channel estimation methods through simulations. Additionally, we compare these methods in terms of their computational complexity. Finally, we validate the performance of the proposed methods through channel measurements conducted in an outdoor environment. The results demonstrate that the proposed methods outperform in-band mmWave channel estimation in terms of spectral efficiency, particularly in scenarios of low SNR and high K-factor.

IEEE Transactions on CommunicationsVol. 73(11)
University of Southern California (US), Georgia Institute of Technology (US), AIT Austrian Institute of Technology GmbH (AT), TU Wien (AT)
National Science Foundation, Marshallplan-Jubiläumsstiftung, Christian Doppler Forschungsgesellschaft
Affordable and clean energy
Openalex Percentile: Top 85%
Millimeter-Wave Propagation and Modeling
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