A Joint Parameter Estimation Method Based on 3D Matrix Pencil for Integration of Sensing and Communication

YANG Xiaolong; ZHANG Bingrui; ZHOU Mu; ZHANG Wen

doi:10.11999/JEIT240003

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YANG Xiaolong, ZHANG Bingrui, ZHOU Mu, ZHANG Wen. A Joint Parameter Estimation Method Based on 3D Matrix Pencil for Integration of Sensing and Communication[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240003

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YANG Xiaolong, ZHANG Bingrui, ZHOU Mu, ZHANG Wen. A Joint Parameter Estimation Method Based on 3D Matrix Pencil for Integration of Sensing and Communication[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240003

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A Joint Parameter Estimation Method Based on 3D Matrix Pencil for Integration of Sensing and Communication

doi: 10.11999/JEIT240003

School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (62101085), The Science and Technology Research Project of Chongqing Jiulongpo District (2022-02-005-Z), Chongqing Graduate Student Research Innovation Project (CYS23457)

Received Date: 2024-01-16
Rev Recd Date: 2024-07-03

Available Online: 2024-08-02

Abstract

Abstract

As a new information communication technology based on software and hardware resource sharing and information sharing, Integration of Sensing and Communication (ISAC) can integrate wireless sensing into Wi-Fi platforms, providing an efficient method for low-cost indoor localization. Focusing on the problem of real-time and accuracy of indoor positioning parameter estimation, a joint parameter estimation algorithm based on three Dimensional (3D) Matrix Pencil (MP) is proposed. First, the Channel State Information (CSI) data is analyzed and a 3D matrix containing Angle of Arrival (AoA), Time of Flight (ToF), and Doppler Frequency Shift (DFS) is constructed. Secondly, the 3D matrix is smoothed and the 3D MP algorithm is used for parameter estimation, the direct path is found by clustering. Finally, the triangulation method is used for positioning to verify the effectiveness of the proposed algorithm. Experimental results show that compared with the MUltiple SIgnal Classification (MUSIC) parameter estimation algorithm, there is no need for complicated peak search steps, and the computational complexity is reduced by 90%. Compared with the two-dimensional MP algorithm, adding DFS can effectively improve the resolution and accuracy of parameter estimation. The actual test verifies that the proposed algorithm can achieve an average positioning accuracy of 0.56 m at a confidence level of 67% indoors. Therefore, the proposed algorithm effectively improves the real-time and accuracy of the existing indoor positioning parameter estimation.
- Integrated Sensing and Communications (ISAC),
- 3D Matrix Pencil (MP),
- Angle of Arrival (AoA),
- Time of Flight (ToF),
- Doppler Frequency Shift (DFS)

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References(31)

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