Channel State Information Restoration and Positioning of massive Multiple Input Multiple Output Integrated Visible Light Communication and Sensing System

LIU Xiaodong; NING Yiting; DONG Fan; TANG Liwei; WANG Yuhao; WANG Jinyuan

doi:10.11999/JEIT231389

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LIU Xiaodong, NING Yiting, DONG Fan, TANG Liwei, WANG Yuhao, WANG Jinyuan. Channel State Information Restoration and Positioning of massive Multiple Input Multiple Output Integrated Visible Light Communication and Sensing System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231389

Citation:

LIU Xiaodong, NING Yiting, DONG Fan, TANG Liwei, WANG Yuhao, WANG Jinyuan. Channel State Information Restoration and Positioning of massive Multiple Input Multiple Output Integrated Visible Light Communication and Sensing System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231389

Citation:

LIU Xiaodong, NING Yiting, DONG Fan, TANG Liwei, WANG Yuhao, WANG Jinyuan. Channel State Information Restoration and Positioning of massive Multiple Input Multiple Output Integrated Visible Light Communication and Sensing System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231389

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Channel State Information Restoration and Positioning of massive Multiple Input Multiple Output Integrated Visible Light Communication and Sensing System

doi: 10.11999/JEIT231389

1.
School of Information Engineering, Nanchang University, Nanchang 330031, China
2.
Digital Technology Application Industry College, Shangrao Normal University, Shangrao 334001, China
3.
School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Funds: The Young Natural Science Foundation of Jiangxi Province (20224BAB212004), The National Natural Science Foundation of China (62061030), The Natural Science Foundation of Jiangsu Province (BK20221328), The Open Project of Key Laboratory of Visible Light Communication (HKLVLC2023-B02), The National Training Program of Innovation and Entrepreneurship for Undergraduates (202210403095)

Received Date: 2023-12-18
Rev Recd Date: 2024-04-03

Available Online: 2024-04-21

Abstract

Abstract

Benefiting from rich spectrum and lamps, Integrated Visible Light Communication and Positioning (IVLCP) systems provide powerful technological solution to meet the high performance communication and positioning in indoor wireless networks. Meanwhile, the massive Multiple Input Multiple Output (m-MIMO) effectively enhance both service coverage and quality of IVLCP systems. However, the channel environment is more complex and the priori information rapidly changed in the m-MIMO-enabled IVLCP systems, making traditional methods challenging for fast and accurate channel estimation and positioning. In order to tackle this challenge, a Channel State Information Restoration and Positioning (CSIRP) network is proposed in this paper. The network not only effectively captures complex distribution feature of channel but also addressing the temporal variations in location, thereby enhancing the robustness and dynamic adaptability of channel and location estimation. Specifically, the CSIRP network employs a conditional generative adversarial process to adaptively train the generator and discriminatorr and thus achieves the channel estimation from received signals. Then, the Long Short-Term Memory(LSTM) is introduced to estimate the location of the receiver from the estimated channel. Simulation results demonstrate that the accuracy of both channel and location estimation achieved by the proposed CSIRP network outperforms existing deep learning benchmark schemes. This provides m-MIMO-enabled IVLCP systems with more reliable and accurate channel state information and positioning.

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References(22)

References

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