Journal
IEEE TRANSACTIONS ON MOBILE COMPUTING
Volume 15, Issue 11, Pages 2907-2920Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TMC.2016.2517630
Keywords
Wi-Fi radar; micro-motion detection; moving pattern recognition; interference cancelation
Funding
- Guangdong Natural Science Funds for Distinguished Young Scholar [S20120011468]
- Shenzhen Science and Technology Foundation [JCYJ20140509172719309, KQCX20150324 160536457]
- China NSFC Grant [61472259]
- Guangdong Young Talent Project [2014TQ01X238]
- Hong Kong RGC [HKUST16207714]
- GDUPS
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Recent literature advances Wi-Fi signals to see people's motions and locations. This paper asks the following question: Can Wi-Fi hear our talks? We present WiHear, which enables Wi-Fi signals to hear our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micromovement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can hear people talks within the radio range. Further, WiHear can simultaneously hear multiple people's talks leveraging MIMO technology. We implement WiHear on both USRP N210 platform and commercial Wi-Fi infrastructure. Results show that within our pre-defined vocabulary, WiHear can achieve detection accuracy of 91 percent on average for single individual speaking no more than six words and up to 74 percent for no more than three people talking simultaneously. Moreover, the detection accuracy can be further improved by deploying multiple receivers from different angles.
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