Information and Communications Technology and Policy

Information and Communications Technology and Policy

Information and Communications Technology and Policy ›› 2026, Vol. 52 ›› Issue (10): 26-39.doi: 10.12267/j.issn.2096-5931.2026.10.004

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Intelligent native channel state information acquisition and standardization for 6G

WANG Jiayin1,2, ZUO Jun1,2, LI Qianrui1,2, HUANG Qiuping1,2, FEI Yongqiang1,2, GAO Qiubin1,2, SUN Shaohui1,2   

  1. 1 CICT Mobile Communications Technology Co., Ltd., Beijing 102208, China
    2 State Key Laboratory of Wireless Mobile Communications, China Academy of Telecommunications Technology, Beijing 100191, China
  • Received:2026-07-20 Online:2026-10-25 Published:2026-10-28

Abstract:

The deep integration of artificial intelligence and communications has emerged as one of the core driving forces advancing wireless communication systems. This paper analyzes the background and motivation of low-overhead channel state information (CSI) acquisition in 6G systems, and proposes low-overhead CSI acquisition methods for 6G systems accordingly, encompassing two categories of schemes: CSI reconstruction based on sparse reference signals and multi-scenario CSI prediction based on a single reference signal. The effectiveness of the proposed schemes is validated through simulations, and their prospects for standardization, along with the critical issues that remain to be addressed, are further discussed.

Key words: deep learning, low-overhead reference signal, channel state information reconstruction, multi-scenario channel state information prediction

CLC Number: