Impacts of Model Mismatch and Array Scale on Channel Estimation for XL-HRIS-Aided Systems

doi:10.12142/ZTECOM.202401004

ZTE Communications ›› 2024, Vol. 22 ›› Issue (1): 24-33.DOI: 10.12142/ZTECOM.202401004

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Impacts of Model Mismatch and Array Scale on Channel Estimation for XL-HRIS-Aided Systems

LU Zhizheng, HAN Yu(), JIN Shi()

National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Received:2024-01-25 Online:2024-03-28 Published:2024-03-28
About author:LU Zhizheng received his BS degree in communications engineering from Nanjing University of Science and Technology, China in 2021. Currently, he is pursuing his PhD degree in information and communications engineering from Southeast University, China. His research interests include extremely large-scale multiple-input multiple-output, near-field channel estimation, and hybrid reconfigurable intelligence surface.
HAN Yu (hanyu@seu.edu.cn) received her BS degree in communications engineering from Hangzhou Dianzi University, China in 2012, and MS and PhD degrees in information and communications engineering from Southeast University, China in 2015 and 2020, respectively. She was a postdoctoral fellow with Singapore University of Technology and Design, Singapore till 2022. Currently, she is an associate professor with Southeast University. Her research interests include extra large-scale MIMO and reconfigurable intelligent surface.
JIN Shi (jinshi@seu.edu.cn) received his BS degree in communications engineering from Guilin University of Electronic Technology, China in 1996, MS degree from Nanjing University of Posts and Telecommunications, China in 2003, and PhD degree in information and communications engineering from Southeast University, China in 2007. From June 2007 to October 2009, he was a research fellow with the Adastral Park Research Campus, University College London, UK. He is currently with the National Mobile Communications Research Laboratory, Southeast University. His research interests include wireless communications, random matrix theory, and information theory. He is serving as an area editor for the Transactions on Communications and IET Electronics Letters. He was an associate editor for the IEEE Transactions on Wireless Communications, IEEE Communications Letters, and IET Communications. Dr. JIN and his co-authors have been awarded the 2011 IEEE Communications Society Stephen O. Rice Prize Paper Award in the field of communication theory, the IEEE Vehicular Technology Society 2023 Jack Neubauer Memorial Award, a 2022 Best Paper Award and a 2010 Young Author Best Paper Award by the IEEE Signal Processing Society. He is an IEEE fellow.
Supported by:
the National Natural Science Foundation of China (NSFC)(62301148);the Natural Science Foundation of Jiangsu Province(BK20230824);the Key Technologies R&D Program of Jiangsu(BE2023022)

Abstract

Abstract:

Extremely large-scale hybrid reconfigurable intelligence surface (XL-HRIS), an improved version of the RIS, can receive the incident signal and enhance communication performance. However, as the RIS size increases, the phase variations of the received signal across the whole array are nonnegligible in the near-field region, and the channel model mismatch, which will decrease the estimation accuracy, must be considered. In this paper, the lower bound (LB) of the estimated parameter is studied and the impacts of the distance and signal-to-noise ratio (SNR) on LB are then evaluated. Moreover, the impacts of the array scale on LB and spectral efficiency (SE) are also studied. Simulation results verify that even in extremely large-scale array systems with infinite SNR, channel model mismatch can still limit estimation accuracy. However, this impact decreases with increasing distance.

Key words: XL-HRIS, near-field, LB, model mismatch, parameter estimation

LU Zhizheng, HAN Yu, JIN Shi. Impacts of Model Mismatch and Array Scale on Channel Estimation for XL-HRIS-Aided Systems[J]. ZTE Communications, 2024, 22(1): 24-33.

Figures/Tables 6

References 36

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Impacts of Model Mismatch and Array Scale on Channel Estimation for XL-HRIS-Aided Systems

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