Name
Abstract | ||
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With the explosive increase in wireless devices, physical-layer signal analysis has become critically beneficial across distinctive domains including interference minimization in network planning, security and privacy (e.g., drone and spycam detection), and mobile health with remote sensing. While SDR is known to be highly effective in realizing such services, they are rarely deployed or used by the end-users due to the costly hardware ~1K USD (e.g., USRP). Low-cost SDRs (e.g., RTL-SDR) are available, but their bandwidth is limited to 2-3 MHz and operation range falls well below 2.4 GHz - the unlicensed band holding majority of the wireless devices. This paper presents SDR-Lite, the first zero-cost, software-only software defined radio (SDR) receiver that empowers commodity WiFi to retrieve the In-phase and Quadrature of an ambient signal. With the full compatibility to pervasively-deployed WiFi infrastructure (without any change to the hardware and firmware), SDR-Lite aims to spread the blessing of SDR receiver functionalities to billions of WiFi users and households to enhance our everyday lives. The key idea of SDR-Lite is to trick WiFi to begin packet reception (i.e., the decoding process) when the packet is absent, so that it accepts ambient signals in the air and outputs corresponding bits. The bits are then reconstructed to the original physical-layer waveform, on which diverse SDR applications are performed. Our comprehensive evaluation shows that the reconstructed signal closely reassembles the original ambient signal (>85% correlation). We extensively demonstrate SDR-Lite effectiveness across seven distinctive SDR receiver applications under three representative categories: (i) RF fingerprinting, (ii) spectrum monitoring, and (iii) (ZigBee) decoding. For instance, in security applications of drone and rogue WiFi AP detection, SDR-Lite achieves 99% and 97% accuracy, which is comparable to USRP.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3372224.3419189 | MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking
London
United Kingdom
September, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7085-1 | 1 |
PageRank | References | Authors |
0.35 | 40 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeong Woo Park | 1 | 74 | 10.92 |
| J. Jung | 2 | 1 | 0.35 |
| Yu-Chiang Frank Wang | 3 | 914 | 61.63 |
| Shuoyu Wang | 4 | 10 | 3.23 |
| Shiwen Yang | 5 | 20 | 3.95 |
| Q. Yan | 6 | 1 | 0.35 |
| Yung Yi | 7 | 1557 | 104.55 |
| Songmin Kim | 8 | 219 | 16.72 |
| J. Jung | 9 | 1 | 0.35 |