ZTE Communications ›› 2022, Vol. 20 ›› Issue (1): 57-62.doi: 10.12142/ZTECOM.202201008

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RIS: Spatial‑Wideband Effect Analysis and Off‑Grid Channel Estimation

JIAN Mengnan1,2(), ZHANG Nan1,2, CHEN Yijian1,2   

  1. 1.State Key Laboratory of Mobile Network and Mobile Multimedia Technology, Shenzhen 518055, China
    2.Algorithm Department, Wireless Product R&D Institute, ZTE Corporation, Shenzhen 518057, China
  • Received:2022-01-24 Online:2022-03-25 Published:2022-04-06
  • About author:JIAN Mengnan (jian.mengnan@zte.com.cn) received the B.E. degree in information engineering from Beijing Institute of Technology, China in 2016, and the M.S. degree from Tsinghua University, China in 2019. She is currently an engineer with ZTE Corporation. Her research interests include reconfigurable intelligent surfaces and orbital angular momentum.|ZHANG Nan received the bachelor degree in communication engineering and the master degree in integrated circuit engineering from Tongji University, China in July 2012 and March 2015, respectively. He is now a senior engineer with ZTE Corporation and works on the standardization of LTE and NR systems. His current research interests include channel modeling, MIMO, NOMA techniques, satellite/ATG communications and reconfigurable intelligent surfaces.|CHEN Yijian received the B.S. degree from Central South University, China in 2006. He is currently a senior engineer with ZTE Corporation. His current research interests include massive MIMO, coordinated multi-point transmission, high-frequency communications, and channel modeling.


As a critical candidate technology for 5G-advanced and 6G, reconfigurable intelligent surfaces (RIS) have received extensive attention from academia and industry. RIS has the promising features of passiveness, reconfigurable ability, and low cost. RIS channel estimation faces the challenges of high matrix dimension, passive estimation, and spatial-wideband effect. In this article, we analyze the impact of the spatial-wideband effect on the RIS channel to account for the propagation delay across RIS elements and estimate sparse channel parameters such as angle and gain through a super-resolution compressive sensing (CS) algorithm. The simulation results explore the influence of the spatial-wideband effect on the RIS channel and verify the effectiveness of the proposed algorithm.

Key words: RIS, channel estimation, spatial-wideband effect, compressed sensing