Physical-Layer CTC From BLE to Wi-Fi With IEEE 802.11ax

Wi-Fi is the de facto standard for providing wireless access to the Internet in the 2.4 GHz ISM band. Tens of billions of Wi-Fi devices (e.g., smartphones) have been shipped worldwide with limited types of wireless radios operating only when Wi-Fi connectivity is available, making it challenging to access data in heterogeneous IoT devices. However, the direct connection between Wireless Personal Area Network (WPAN) technologies, such as Bluetooth, and Wi-Fi presents challenges due to the inherent distinct physical layer. In our work, a novel communication method called BlueWi has been introduced, which serves as a cross technology communication method that enables BLE devices to establish connections and engage in communication with Wi-Fi based WPAN networks. We let BLE signals hitchhike on ongoing Wi-Fi signals, enabling Wi-Fi to recognize specific BLE signal waveforms in the frequency domain. By analyzing the decoded Wi-Fi payload, BlueWi can retrieve the BLE data, ensuring this method remains fully compatible with existing commodity Wi-Fi hardware. The direct sequence spread spectrum scheme is appended to handle general BLE frames and can be considered as “<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">COPY</i>” operation, which allows for better correlation and detection of the signal at the receiver. Evaluations conducted using both USRP and commodity devices have demonstrated that BlueWi can achieve concurrent wireless communication from BLE commercial chips to Wi-Fi networks with a frame reception rate exceeding 96%.

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2024-09-17
DOI
https://doi.org/10.1109/tmc.2024.3462941
Citations
18
Primary Topic
Wireless Sensor Networks for Data Analysis
Type
article
Field-Weighted Citation Impact
6.28
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article

Physical-Layer CTC From BLE to Wi-Fi With IEEE 802.11ax

Demin Gao, Ruofeng Liu, Tian He, Yongrui Chen et al.
18 citations
IEEE Transactions on Mobile Computing
Wireless Sensor Networks for Data Analysis
6.28
article

Physical-Layer CTC From BLE to Wi-Fi With IEEE 802.11ax

Demin Gao, Ruofeng Liu, Tian He, Yongrui Chen, Yunhuai Liu, Liyuan Ou, Xiuzhen Guo
article en
18 citations

Abstract

Wi-Fi is the de facto standard for providing wireless access to the Internet in the 2.4 GHz ISM band. Tens of billions of Wi-Fi devices (e.g., smartphones) have been shipped worldwide with limited types of wireless radios operating only when Wi-Fi connectivity is available, making it challenging to access data in heterogeneous IoT devices. However, the direct connection between Wireless Personal Area Network (WPAN) technologies, such as Bluetooth, and Wi-Fi presents challenges due to the inherent distinct physical layer. In our work, a novel communication method called BlueWi has been introduced, which serves as a cross technology communication method that enables BLE devices to establish connections and engage in communication with Wi-Fi based WPAN networks. We let BLE signals hitchhike on ongoing Wi-Fi signals, enabling Wi-Fi to recognize specific BLE signal waveforms in the frequency domain. By analyzing the decoded Wi-Fi payload, BlueWi can retrieve the BLE data, ensuring this method remains fully compatible with existing commodity Wi-Fi hardware. The direct sequence spread spectrum scheme is appended to handle general BLE frames and can be considered as “<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">COPY</i>” operation, which allows for better correlation and detection of the signal at the receiver. Evaluations conducted using both USRP and commodity devices have demonstrated that BlueWi can achieve concurrent wireless communication from BLE commercial chips to Wi-Fi networks with a frame reception rate exceeding 96%.

IEEE Transactions on Mobile ComputingVol. 24(1)
University of Minnesota (US), Nanjing Forestry University (CN), Peking University (CN), Zhejiang University-University of Edinburgh Institute (CN), University of Chinese Academy of Sciences (CN), Zhejiang University (CN), Michigan State University (US)
Affordable and clean energy
Openalex Percentile: Top 3%
Wireless Sensor Networks for Data Analysis
6.28
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