Xuyu Wang

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With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this paper, we present a novel deep learning based indoor fingerprinting system using Channel State Information (CSI), which is termed DeepFi. Based on three hypotheses on(More)
—With the increasing demand of location-based services , indoor localization based on fingerprinting has become an increasingly important technique due to its high accuracy and low hardware requirement. In this paper, we propose PhaseFi, a fingerprinting system for indoor localization with calibrated channel state information (CSI) phase information. In(More)
With the proliferation of mobile devices such as smartphones, an interesting problem is how to make use them to improve the accuracy of localization in indoor environments. In this paper, we develop a novel cooperative localization scheme exploiting mobility in the indoor environment. The problem is formulated as a semidefinite program (SDP) using Linear(More)
—With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this paper, we present a novel deep learning based indoor fingerprinting system using Channel State Information (CSI), which is termed DeepFi. Based on three hypotheses on(More)
With the increasing demand of location-based services, indoor localization based on fingerprinting has become an increasingly important technique due to its high accuracy and low hardware requirement. In this paper, we propose PhaseFi, a fingerprinting system for indoor localization with calibrated channel state information (CSI) phase information. In(More)
With the rapid growth of mobile data, many LTE operators are interested in leveraging unlicensed bands to enhance data rates and user experience. Th is paper investigates the problem of the coexistence of LTE and Wi-Fi in 5 GHz unlicensed bands. We fi rst introduce the current rules for the 5 GHz unlicensed bands and the carrier aggregation technique. We(More)
With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this thesis, we present a novel deep learning based indoor fingerprinting system using Channel State Information (CSI), which is termed DeepFi. Based on three hypotheses on(More)
In future communication system, the demand for high capacity is a challenging problem for wireless services, especially for delivery of the 'last mile'. A potential solution is offered by the high altitude platforms (HAPs), which can utilize the best character and tradeoff of both satellite and terrestrial networks. Since the performance of the HAPs depends(More)
Breathing signal monitoring can provide important clues for human's physical health problems. Comparing to existing techniques that require wearable devices and special equipment, a more desirable approach is to provide contact-free and long-term breathing rate monitoring by exploiting wireless signals. In this paper , we propose TensorBeat, a system to(More)