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Native WiFi Backscatter

delete2024-10-01
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PRE
AI
L
Longzhi Yuan
W
Wei Gong
Y
Yuguang Fang *
DOI:10.1109/TNET.2024.3409081delete
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摘要

摘要

En 中文
WiFi backscatter has attracted intensive attention because the large population of WiFi radios can provide plenty of excitation signals. However, WiFi backscatter communication has imposed unwanted constraints on either exciters or receivers since its inception. In this paper, we present Chameleon, a native WiFi backscatter system, where WiFi tags can generate native WiFi packets using uncontrolled productive WiFi signals as carriers. Our tag-only design requires no particular excitation patterns and no changes in software/hardware on WiFi network interface cards (NICs). The key idea is for the Chameleon tag to demodulate the productive WiFi signal and backscatter it into a full-function packet using on-the-fly modulation. To align tag decoding and modulation with excitation symbols, we design a time synchronization and clock compensation scheme suitable for low-power tags. We prototype WiFi tags using ultra-low-power FPGAs and evaluate them in real-world scenarios where excitations are ambient traffic and backscatter receivers are a wide range of commercial off-the-shelf (COTS) NICs. Comprehensive field studies show that the maximal backscatter throughput of Chameleon is almost 1 Mbps, which is over 125 x and 1000 x higher than what WiTAG and FS-Backscatter tags could achieve, respectively. We also show that Chameleon can natively communicate with various COTS WiFi devices on Windows, iOS, and Android platforms. We believe that this design will enable ubiquitous WiFi connectivity for billions of IoT devices via widely available mobile gadgets and existing wireless infrastructure.
Keyword:
Wireless fidelity
Backscatter
Symbols
Receivers
Demodulation
Throughput
Synchronization
Internet of Things (IoT)
backscatter
low power

期刊

I
IEEE-ACM Transactions on Networking
IF:
3.6
论文数:
4.4K
被引数:
9.5K

机构

C
City University of Hong Kong
学者数:
2.3W
论文数: 3.0W
被引数: 6.1W
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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