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%.
Authors
- Demin Gao (ORCID: https://orcid.org/0000-0002-6704-8979)
- Ruofeng Liu (ORCID: https://orcid.org/0000-0001-9804-3727)
- Tian He (ORCID: https://orcid.org/0000-0001-6062-2619)
- Yongrui Chen (ORCID: https://orcid.org/0000-0002-4618-8403)
- Yunhuai Liu (ORCID: https://orcid.org/0000-0002-1180-8078)
- Liyuan Ou
- Xiuzhen Guo (ORCID: https://orcid.org/0000-0002-8655-8130)
Institutions
- 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)
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