Identification of LOS Clusters in Power Angular Spectrum for Indoor Localization Compatible with Communication at Millimeter Band

LÜ Pengfei; SARRAZIN Julien; HUANG Mo

doi:10.11999/JEIT220786

Volume 45 Issue 7

Jul. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(7): 2467-2475

LÜ Pengfei, SARRAZIN Julien, HUANG Mo. Identification of LOS Clusters in Power Angular Spectrum for Indoor Localization Compatible with Communication at Millimeter Band[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2467-2475. doi: 10.11999/JEIT220786

Citation:

LÜ Pengfei, SARRAZIN Julien, HUANG Mo. Identification of LOS Clusters in Power Angular Spectrum for Indoor Localization Compatible with Communication at Millimeter Band[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2467-2475. doi: 10.11999/JEIT220786

Citation:

LÜ Pengfei, SARRAZIN Julien, HUANG Mo. Identification of LOS Clusters in Power Angular Spectrum for Indoor Localization Compatible with Communication at Millimeter Band[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2467-2475. doi: 10.11999/JEIT220786

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Identification of LOS Clusters in Power Angular Spectrum for Indoor Localization Compatible with Communication at Millimeter Band

doi: 10.11999/JEIT220786

1.
Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Sorbonne Université Paris, 75252, France

Funds: The National Natural Science Foundation of China (61501454)

Received Date: 2022-06-15
Rev Recd Date: 2023-05-19

Available Online: 2023-06-12

Publish Date: 2023-07-10

Abstract

Abstract

An identification method of Line-of-Sight (LOS) propagation for indoor localization at millimeter band is proposed in this paper. Based on beam training process, the proposed method identifies the LOS clusters in power angular spectrum. After clustering the Power Angular Spectrum (PAS), the statistical characteristics of five different channel metrics intra-clusters, namely the spatial-domain symmetry, kurtosis of impulse response and transfer function, mean excess delay, and Root Mean Square (RMS) delay spread, are analyzed using maximum likelihood ratio and artificial neural network. A noticeable difference between LOS and Non- Line-of-Sight (NLOS) clusters is observed, and validated with measurement.
- Indoor localization,
- Line-of-Sight (LOS) identification,
- Millimeter wave,
- Channel angular clustering,
- Watershed segmentation

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References(17)

References

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