University of Oulu

J. He, M. Leinonen, H. Wymeersch and M. Juntti, "Channel Estimation for RIS-Aided mmWave MIMO Systems," GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020, pp. 1-6, doi: 10.1109/GLOBECOM42002.2020.9348112

Channel estimation for RIS-aided mmWave MIMO systems

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Author: He, Jiguang1; Leinonen, Markus1; Wymeersch, Henk2;
Organizations: 1Centre for Wireless Communications, FI-90014, University of Oulu, Finland
2Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2021-02-17


A reconfigurable intelligent surface (RIS) can shape the radio propagation by passively changing the directions of impinging electromagnetic waves. The optimal control of the RIS requires perfect channel state information (CSI) of all the links connecting the base station (BS) and the mobile station (MS) via the RIS. Thereby the channel (parameter) estimation at the BS/MS and the related message feedback mechanism are needed. In this paper, we adopt a two-stage channel estimation scheme for the RIS-aided millimeter wave (mmWave) MIMO channels using an iterative reweighted method to sequentially estimate the channel parameters. We evaluate the average spectrum efficiency (SE) and the RIS beamforming gain of the proposed scheme and demonstrate that it achieves high-resolution estimation with the average SE comparable to that with perfect CSI.

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Series: IEEE Global Communications Conference
ISSN: 2334-0983
ISSN-E: 2576-6813
ISSN-L: 2334-0983
ISBN: 978-1-7281-8298-8
ISBN Print: 978-1-7281-8299-5
Article number: 9348112
DOI: 10.1109/GLOBECOM42002.2020.9348112
Host publication: GLOBECOM 2020 - 2020 IEEE Global Communications Conference
Conference: IEEE Global Communications Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is supported by Horizon 2020, European Union’s Framework Programme for Research and Innovation, under grant agreement no. 871464 (ARIADNE). This work is also partially supported by the Academy of Finland 6Genesis Flagship (grant 318927) and Swedish Research Council (grant no. 2018-03701). The work of M. Leinonen has been financially supported in part by Infotech Oulu and the Academy of Finland (grant 319485 and 323698).
EU Grant Number: (871464) ARIADNE - Artificial Intelligence Aided D-band Network for 5G Long Term Evolution
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
319485 (Academy of Finland Funding decision)
323698 (Academy of Finland Funding decision)
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