Codebook design and beam training for extremely large-scale RIS: Far-field or near-field?

Reconfigurable intelligent surface (RIS) is more likely to develop into extremely large-scale RIS (XL-RIS) to efficiently boost the system capacity for future 6G communications. Beam training is an effective way to acquire channel state information (CSI) for XL-RIS. Existing beam training schemes re...

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Bibliographic Details
Published inChina communications Vol. 19; no. 6; pp. 193 - 204
Main Authors Wei, Xiuhong, Dai, Linglong, Zhao, Yajun, Yu, Guanghui, Duan, Xiangyang
Format Journal Article
LanguageEnglish
Published China Institute of Communications 01.06.2022
Beijing National Research Center for Information Science and Technology(BNRist)as well as the Department of Electronic Engineering,Tsinghua University,Beijing 100084,China%ZTE Corporation,Shenzhen 518038,China
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Summary:Reconfigurable intelligent surface (RIS) is more likely to develop into extremely large-scale RIS (XL-RIS) to efficiently boost the system capacity for future 6G communications. Beam training is an effective way to acquire channel state information (CSI) for XL-RIS. Existing beam training schemes rely on the far-field codebook. However, due to the large aperture of XL-RIS, the scatters are more likely to be in the near-field region of XL-RIS. The far-field codebook mismatches the near-field channel model. Thus, the existing far-field beam training scheme will cause severe performance loss in the XL-RIS assisted near-field communications. To solve this problem, we propose the efficient near-field beam training schemes by designing the near-field codebook to match the near-field channel model. Specifically, we firstly design the near-field codebook by considering the near-field cascaded array steering vector of XL-RIS. Then, the optimal codeword for XL-RIS is obtained by the exhausted training procedure. To reduce the beam training overhead, we further design a hierarchical near-field codebook and propose the corresponding hierarchical near-field beam training scheme, where different levels of sub-codebooks are searched in turn with reduced codebook size. Simulation results show the proposed near-field beam training schemes outperform the existing far-field beam training scheme.
ISSN:1673-5447
DOI:10.23919/JCC.2022.06.015