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Semi-Blind Channel Estimation for RIS-Assisted MISO Systems Using Expectation Maximization
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DOI：10.1109/TVT.2022.3182347.png)
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摘要
En 中文
Reconfigurable intelligent surface (RIS) is a passive antenna array composed of a large number of reflecting elements. In a RIS-assisted communication system, it is a challenging task to acquire accurate channel state information (CSI). In this paper, we propose a semi-blind channel estimation method for a RIS-assisted massive multiple-input single-output (MISO) system. Assuming a Gaussian priori on the data symbols, an iterative expectation maximization (EM)-based algorithm is developed to obtain the maximum likelihood (ML) estimate of the cascaded RIS channel. Different from existing pilot-based methods, the proposed semi-blind channel estimation method exploits the data symbols for channel estimation enhancement and only a fraction of full-pilot signaling overhead is required. Simulation results verify that the proposed method achieves significant improvement in the accuracy of the channel estimation while it noticeably reduces the training pilot overhead.
Keyword:
Channel estimation
Symbols
Maximum likelihood estimation
MISO communication
Training
Symmetric matrices
Discrete Fourier transforms
Channel estimation
expectation maximization (EM)
re- configurable intelligent surface (RIS)
semi-blind
期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
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引用论文
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