Joint Effective Channel Estimation and Data Detection for RIS-Aided Massive MIMO Systems With Low-Resolution ADCs

This letter investigates the uplink data detection for reconfigurable intelligent surface (RIS)-assisted massive multiple-input multiple-output (MIMO) systems with low-resolution quantization at the base stations (BSs). By exploiting the statistical characteristics of the user-to-RIS and RIS-to-BS c...

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Bibliographic Details
Published in:IEEE communications letters 2023-02, Vol.27 (2), p.721-725
Main Authors: Xiong, Youzhi, Qin, Lang, Sun, Sanshan, Liu, Li, Mao, Sun, Zhang, Zhongpei, Wei, Ning
Format: Article
Language:English
Subjects:
Algorithms
bilinear generalized approximate message passing
Central limit theorem
Channel estimation
low-resolution quantization
Massive MIMO
Measurement
Message passing
MIMO communication
Quantization (signal)
Random variables
Reconfigurable intelligent surface
Sun
System effectiveness
Wireless communication
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Summary:This letter investigates the uplink data detection for reconfigurable intelligent surface (RIS)-assisted massive multiple-input multiple-output (MIMO) systems with low-resolution quantization at the base stations (BSs). By exploiting the statistical characteristics of the user-to-RIS and RIS-to-BS channels and the central limit theorem (CLT), we first demonstrate that the components in the effective channel are approximately Gaussian distributed under propagation in sub-6 GHz bands. Based on the bilinear generalized approximate message passing (BiG-AMP) algorithm, we then provide a quantization-aware approach to estimate the effective channel and recover transmit symbols. Finally, numerical results show that the revised BiG-AMP technique can improve the performance of channel estimation and data detection with affordable computational complexity.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2022.3232217