A Low Complexity Millimeter Wave Channel Estimation Algorithm in Reconfigurable Intelligent Surface

PU Xumin; SUN Zhinan; LI Jingjie; HUANG Qiong; CHEN Qianbin

doi:10.11999/JEIT211602

Volume 44 Issue 7

Jul. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(7): 2281-2288

PU Xumin, SUN Zhinan, LI Jingjie, HUANG Qiong, CHEN Qianbin. A Low Complexity Millimeter Wave Channel Estimation Algorithm in Reconfigurable Intelligent Surface[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2281-2288. doi: 10.11999/JEIT211602

Citation:

PU Xumin, SUN Zhinan, LI Jingjie, HUANG Qiong, CHEN Qianbin. A Low Complexity Millimeter Wave Channel Estimation Algorithm in Reconfigurable Intelligent Surface[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2281-2288. doi: 10.11999/JEIT211602

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A Low Complexity Millimeter Wave Channel Estimation Algorithm in Reconfigurable Intelligent Surface

doi: 10.11999/JEIT211602

PU Xumin^{1, 2, 3
,
,},
SUN Zhinan¹,
LI Jingjie¹,
HUANG Qiong¹,
CHEN Qianbin²

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing Key Laboratory of Mobile Communications Technology, Chongqing 400065, China
3.
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Funds: The National Natural Science Foundation of China (61701062), The China Postdoctoral Science Foundation (2019M651649), The Jiangsu Planned Projects for Postdoctoral Research Funds (2018K041c),The Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202100649)

Received Date: 2021-12-30
Rev Recd Date: 2022-06-09

Available Online: 2022-06-20

Publish Date: 2022-07-25

Abstract

Abstract

In this paper, a low complexity channel estimation algorithm is proposed, which is used to reduce the computational complexity of the millimeter wave channel estimation in the massive MIMO systems assisted by the Reconfigurable Intelligent Surfaces (RIS). In the proposed scheme, some elements of the RIS are connected to the Radio Frequency (RF) chain to estimate the channel between the base station/user and the RIS separately, which improves the flexibility of channel estimation. The zero-padding two-Dimensional Fast Fourier Transform (2D-FFT) algorithm is used for angle estimation in this scenario for the first time. The path gain estimation is obtained by using the spectral peak of the two-dimensional spatial spectrum of the signal and its corresponding argument. Simulation results show that the proposed algorithm achieves excellent channel estimation performance, and based on the system parameter setting to ensure the channel estimation performance, the proposed algorithm has a strong complexity advantage.
- Channel estimation,
- Reconfigurable Intelligent Surfaces(RIS),
- Massive MIMO,
- Low complexity

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References(24)

References

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