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ZTE Communications ›› 2024, Vol. 22 ›› Issue (1): 41-52.DOI: 10.12142/ZTECOM.202401006

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  • 收稿日期:2023-12-19 出版日期:2024-03-29 发布日期:2024-03-28

Near-Field Beam Training for Holographic MIMO Communications: Typical Methods, Challenges and Future Directions

SHEN Jiayu1, YANG Jun2, ZHU Chen3, DENG Zhiji4, HUANG Chongwen1()   

  1. 1.Zhejiang University, Hangzhou 310058, China
    2.ZTE Corporation, Shenzhen 518055, China
    3.Polytechnic Institute, Zhejiang University, Hangzhou 310015, China
    4.Zhejiang Dahua Technology Co. , Ltd. , Hangzhou 310053, China
  • Received:2023-12-19 Online:2024-03-29 Published:2024-03-28
  • About author:SHEN Jiayu is currently pursuing his BS degree with the College of Information Science and Electronic Engineering at Zhejiang University, China. His research interests focus on near-field communications.
    YANG Jun received his BS degree in geophysics from the China University of Geosciences (Wuhan), China in 2011 and the joint-training PhD degree in geophysics from the University of Science and Technology of China and the University of North Carolina, USA in 2016. He is currently a senior algorithm engineer with ZTE Corporation. His research interests include reconfigurable intelligent surfaces, MIMO communications and computational electromagnetics.
    ZHU Chen received his BS degree from North University of China in 2010, and MS degree from Zhejiang University of Technology, China in 2013. He is currently engaged in teaching and research at the College of Engineering, Zhejiang University, China. His main research interests include general sense computing integration, machine learning, image processing, and cloud-edge collaborative computing.
    DENG Zhiji received his BS degree in communication engineering from Xiamen University in 2008. He is now working in Zhejiang Dahua Technology Co., Ltd., as the president of Central Research Institute/Future Communication Research Institute. His main research interests include global multidimensional sensing and large-scale video networking. He has hosted and participated in eight major scientific research projects at the national and ministerial levels. He has won multiple first and second prizes in science and technology awards at the provincial, ministerial, and national levels. He has won the titles of “High Level Talents” of Zhejiang Province, “Model Worker” of Binjiang, “Outstanding Invention Talent” of the Provincial Invention Association, “Outstanding Engineer” of the China Software Industry Association, etc. He has dominated four international standards of ITU-T and 10 industry standards, and has applied for 270 patents.
    HUANG Chongwen (chongwenhuang@zju.edu.cn) received his BS degree from the Binhai College, Nankai University, China in 2010, and MS degree from the University of Electronic Science and Technology of China in 2013. He had worked with the Institute of Electronics, Chinese Academy of Sciences (IECAS) as a research engineer since July 2013. From September 2015, he had started his PhD journey with Singapore University of Technology and Design (SUTD), and CentraleSupélec University, France under the supervision of Prof. Chau YUEN and Prof. Mérouane DEBBAH. From October 2019 to September 2020, he was a post-doctoral researcher at SUTD. Since September 2020, he has been working with Zhejiang University, China as a tenure-track young professor. His main research interests include holographic MIMO surface/reconfigurable intelligent surface, B5G/6G wireless communications, mmWave/THz communications, and deep learning technologies for wireless communications. He was a recipient of the IEEE Marconi Prize Paper Award in wireless communications in 2021. He received the Singapore Government PhD Scholarship and PHC Merlion PhD Grant (2016–2019) for studying in CentraleSupélec, France. In addition, he has served as the chair of several wireless communications flagship conferences, including the session chair of 2021 IEEE WCNC, 2021 IEEE VTC-Fall, and the symposium chair of IEEE WCSP 2021.

Abstract:

Holographic multiple-input multiple-output (HMIMO) has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems. The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios. Beam training as a key technique for wireless communication is worth exploring in this near-field scenario. Compared with the widely researched far-field beam training, the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm. In this paper, we introduce several typical near-field beam training methods: exhaustive beam training, hierarchical beam training, and multi-beam training that includes equal interval multi-beam training and hash multi-beam training. The performances of these methods are compared through simulation analysis, and their effectiveness is verified on the hardware testbed as well. Additionally, we provide application scenarios, research challenges, and potential future research directions for near-field beam training.

Key words: holographic multiple-input multiple-output (HMIMO), beam training, near-field, equal interval multi-beam (EIMB) training, hash multi-beam (HMB) training