A Tensor-Based Joint AoA and ToF Estimation Method for Wi-Fi Systems

This letter presents a tensor-based joint AoA and ToF estimation method using the channel state information for Wi-Fi systems. Our method can mitigate the estimation error caused by the signal phase offset and noise interference using linear regression and discrete wavelet transform, respectively. M...

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Bibliographic Details
Published inIEEE wireless communications letters Vol. 10; no. 11; pp. 2543 - 2546
Main Authors Zhao, Bobai, Hu, Keke, Gong, Yubing, Shen, Yuan
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
angle-of-arrival
Antenna measurements
Discrete Wavelet Transform
Estimation
Linear antenna arrays
Location awareness
Lower bounds
Mathematical analysis
Multipath propagation
Performance evaluation
tensor decomposition
Tensors
time-of-flight
Wavelet transforms
Wireless communication
Wireless fidelity
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Summary:This letter presents a tensor-based joint AoA and ToF estimation method using the channel state information for Wi-Fi systems. Our method can mitigate the estimation error caused by the signal phase offset and noise interference using linear regression and discrete wavelet transform, respectively. Moreover, the Cramér-Rao lower bound for joint AoA and ToF estimation is derived for performance evaluation. Finally, Wi-Fi measurements are taken in indoor scenarios, and the numerical results show that the proposed method can reduce the estimation errors by more than 20% in comparison with existing algorithms.
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2021.3106699