T
Tony Xiao Han
Researcher at Huawei
Publications - 9
Citations - 283
Tony Xiao Han is an academic researcher from Huawei. The author has contributed to research in topics: Radar & Communications system. The author has an hindex of 3, co-authored 9 publications receiving 24 citations.
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Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond
TL;DR: In this paper, the authors provide a comprehensive overview on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC).
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A Survey on Fundamental Limits of Integrated Sensing and Communication
An Liu,Zhe Huang,Min Li,Yubo Wan,Wenrui Li,Tony Xiao Han,Chenchen Liu,Rui Du,Danny Tan Kai Pin,Jianmin Lu,Yuan Shen,Fabiola Colone,Kevin Chetty +12 more
TL;DR: In this paper, the authors provide a comprehensive survey for the current research progress on the fundamental limits of integrated sensing and communication (ISAC), and summarize the major performance metrics and fundamental limits used in sensing, communications and ISAC, respectively.
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Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model
TL;DR: A deep spectrogram network (DSN) is proposed by leveraging the residual mapping technique to enhance the HMR performance and a primitive based autoregressive hybrid (PBAH) channel model is developed, which facilitates efficient training and testing dataset generation for HMR in a virtual environment.
Proceedings ArticleDOI
Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model
TL;DR: Wang et al. as discussed by the authors proposed a deep spectrogram network (DSN) by leveraging the residual mapping technique to enhance the human motion recognition (HMR) performance, which facilitates efficient training and testing dataset generation for HMR in a virtual environment.
Journal ArticleDOI
Moving Target Localization and Activity/Gesture Recognition for Indoor Radio Frequency Sensing Applications
TL;DR: In this article, a dual-frequency continuous wave radar is proposed to achieve both localization and activity/ gesture recognition simultaneously, where features of different movements will be classified by the activity and gesture recognition network (AGRNet) which is a lightweight network based on MobileNet.