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Open Access

Performance analysis of reconfigurable intelligent surface assisted systems under channel aging (invited paper)

School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, Australia
ZTE Corporation, and State Key Laboratory of Mobile Network and Mobile Multimedia Technology, Shenzhen 518057, China
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
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Abstract

Reconfigurable intelligent surfaces (RISs) have attracted significant attention due to their capability in customizing wireless communication environments to improve system performance. In this study, we investigate the performance of an RIS-assisted multi-user multiple-input single-output wireless communication system, considering the impact of channel aging caused by users’ relative movements. In particular, first, we propose a model incorporating the joint effects of channel aging and channel estimation errors to investigate the performance of the RIS-assisted system. Then, we derive novel closed-form expressions for characterizing the sum spectral efficiency with zero-forcing precoding. From our analysis, we unveil that an increase in the temporal channel correlation coefficient, the number of base station antennas, and the received power at the users could help improve system performance. Furthermore, increasing the number of reflecting elements M of the RIS generally yields a good system performance, but with a diminishing return when M is sufficiently large. Finally, simulation results are presented to validate the accuracy of the analytical results.

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Intelligent and Converged Networks
Pages 74-85
Cite this article:
Zhang Y, Zhang J, Ng DWK, et al. Performance analysis of reconfigurable intelligent surface assisted systems under channel aging (invited paper). Intelligent and Converged Networks, 2022, 3(1): 74-85. https://doi.org/10.23919/ICN.2022.0002

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Received: 08 December 2021
Revised: 20 January 2022
Accepted: 11 February 2022
Published: 30 March 2022
© All articles included in the journal are copyrighted to the ITU and TUP.

This work is available under the CC BY-NC-ND 3.0 IGO license:https://creativecommons.org/licenses/by-nc-nd/3.0/igo/

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