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Cited by 61Advanced Wireless Communication TechnologiesAdvanced Antenna and Metasurface TechnologiesMillimeter-Wave Propagation and Modeling

Channel Estimation for Stacked Intelligent Metasurface-Assisted Wireless Networks

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Yao, Xianghao, An, Jiancheng, Gan, Lu, Di Renzo, Marco, Yuen, Chau·2024·IEEE Wireless Communications Letters
DOI 10.1109/lwc.2024.3369874
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Abstract

Emerging technologies, such as holographic multiple-input multiple-output (HMIMO) and stacked intelligent metasurface (SIM), are driving the development of wireless communication systems. Specifically, the SIM is physically constructed by stacking multiple layers of metasurfaces and has an architecture similar to an artificial neural network (ANN), which can flexibly manipulate the electromagnetic waves that propagate through it at the speed of light. This architecture enables the SIM to achieve HMIMO precoding and combining in the wave domain, thus significantly reducing the hardware cost and energy consumption. In this letter, we investigate the channel estimation problem in SIM-assisted multi-user HMIMO communication systems. Since the number of antennas at the base station (BS) is much smaller than the number of meta-atoms per layer of the SIM, it is challenging to acquire the channel state information (CSI) in SIM-assisted multi-user systems. To address this issue, we collect multiple copies of the uplink pilot signals that propagate through the SIM. Furthermore, we leverage the array geometry to identify the subspace that spans arbitrary spatial correlation matrices. Based on partial CSI about the channel statistics, a pair of subspace-based channel estimators are proposed. Additionally, we compute the mean square error (MSE) of the proposed channel estimators and optimize the phase shifts of the SIM to minimize the MSE. Numerical results are illustrated to analyze the effectiveness of the proposed channel estimation schemes.

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  • Installing a SIM on a LEO satellite would significantly reduce the processing delay and computing load of the satellite compared to traditional digital beamforming methods.

    “This would significantly reduce the processing delay and computing load of the satellite compared to traditional digital beamforming methods.”

    From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [91]

    The Introduction states that an SIM greatly reduces precoding delay compared with its digital counterpart and decreases the number of RF chains. It does not address installation on a LEO satellite or establish a reduction in the satellite’s computing load; the system studied uses a base station and user equipment. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 22

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Sorted by citations

Authors
Yao, X., An, J., Gan, L., Di Renzo, M., & Yuen, C.
Affiliations
  • University of Electronic Science and Technology of China (CN)
  • Nanyang Technological University (SG)
  • Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des Signaux et Systèmes, Gif-sur-Yvette, France
ORCID
Venue
IEEE Wireless Communications Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2024-05
Volume
13
Issue
5
Pages
1349-1353
ISSN
  • 2162-2337 (ISSN-L)
  • 2162-2345
DOI
10.1109/lwc.2024.3369874
OpenAlex
W4392151992
Cited by
61
References
2
Citations by year
2026: 19 · 2025: 37 · 2024: 5
FWCI
6.33
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Wireless Communications Letters (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • DR-NTU (Nanyang Technological University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • Sichuan Science and Technology Program (2023YFSY0008, 2023YFG0291)
  • Yibin Science and Technology Program (YBP-002)
  • Horizon Europe Projects (COVER-101086228, UNITE-101129618, INSTINCT-101139161)
  • ANR Projects (NF-PERSEUS 22-PEFT-004, PASSIONATE ANR-23-CHR4-0003-01)
  • Ministry of Education, Singapore, under its MOE Tier 2 (MOE-T2EP50220-0019)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
  • Physical Sciences › Engineering › Aerospace Engineering › Advanced Antenna and Metasurface Technologies
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
Keywords
stacked intelligent metasurfaces, channel estimation, holographic MIMO, multi-user MIMO, subspace-based estimation, spatial correlation matrix, phase shift optimization, channel state information

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