Cellular Signal CSI and DoA Based Fingerprint Positioning With Adaptive Information Fusion

In this paper, with cellular signals available, we propose a channel state information (CSI) and direction of arrival (DoA) fusion based fingerprint positioning method for mobile terminals. The functions taking CSI and DoA matching Euclidean distances as the arguments are designed to update the Euclidean distance calculation for the CSI and DoA fusion fingerprint. The functions are adaptive to the signal measurement statistics. A Bayes' rule based weight updating method for Weighted K-Nearest Neighbors (WKNN) algorithm is developed, called B-WKNN algorithm, which is employed to determine the mobile terminal position. Simulations are conducted to verify the performance of the proposed method, and the results show that it outperforms other fingerprint based positioning methods in terms of positioning accuracy.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-08-25
DOI
https://doi.org/10.1109/tvt.2025.3602444
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
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article

Cellular Signal CSI and DoA Based Fingerprint Positioning With Adaptive Information Fusion

Xiukui Li
IEEE Transactions on Vehicular Technology
Biometric Identification and Security
article

Cellular Signal CSI and DoA Based Fingerprint Positioning With Adaptive Information Fusion

Xiukui Li
article en

Abstract

In this paper, with cellular signals available, we propose a channel state information (CSI) and direction of arrival (DoA) fusion based fingerprint positioning method for mobile terminals. The functions taking CSI and DoA matching Euclidean distances as the arguments are designed to update the Euclidean distance calculation for the CSI and DoA fusion fingerprint. The functions are adaptive to the signal measurement statistics. A Bayes' rule based weight updating method for Weighted K-Nearest Neighbors (WKNN) algorithm is developed, called B-WKNN algorithm, which is employed to determine the mobile terminal position. Simulations are conducted to verify the performance of the proposed method, and the results show that it outperforms other fingerprint based positioning methods in terms of positioning accuracy.

IEEE Transactions on Vehicular TechnologyVol. 75(2)
Dalian University of Technology (CN)
Openalex Percentile: Top 73%
Biometric Identification and Security
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