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\begin{document}

\title{Cross-domain extendable gesture recognition system using WiFi signals}



\author[1]{Yuxi Qin}%
\author[1]{Su Pan}%
\author[2]{Zibo Li}%
\affil[1]{Nanjing University of Posts and Telecommunications}%
\affil[2]{Nanjing Tech University}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\begin{abstract}
This letter proposes a cross-domain WiFi-based gesture recognition
system (WiCross) based on a dynamically weighted multi-label generative
adversarial network. Most existing WiFi-based gesture recognition
systems are user, orientation, and environment sensitive, which limits
the application of WiFi sensing. Compared with the influence of users
and environments on WiFi sensing systems, the influence of orientation
on WiFi sensing systems is more difficult to remove. To alleviate the
confusion caused by the orientation more effectively, we arrange the
transmitting and receiving antennas according to the characteristics of
the Fresnel region. We propose to dynamically weight different links
according to users' orientations and use a multi-label generative
adversarial network to obtain domain-independent features. More
importantly, WiCross can use domain-independent features to classify
some unknown gestures without modifying any code or data set.
Lightweight computing resource consumption allows WiCross to respond in
real-time. The experimental results show that WiCross can achieve an
in-domain recognition accuracy of 93.54\% and a cross-domain recognition
accuracy of 93.11\%%
\end{abstract}%



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