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Enabling High-rate Backscatter Sensing at Scale

Mingqi Xie, Meng Jin, Fengyuan Zhu, Yuzhe Zhang, Xiaohua Tian, Xinbing Wang, Chenghu Zhou

2024Year
5Citations
1Top-tier citations

Abstract

This paper presents μTag, an ultra-low-power backscatter sensor that supports high-frequency sensing of a large number of targets simultaneously. The core of μTag is an RF "gene editing" technique that embeds both the identity of the sensor and the real-time motion state of the attached target intensively in the transient features of the sensor's RF signal, in a collision-resilient manner. We provide practical techniques which i) generate such "genetic signal" with purely analog and extremely simple circuits; and ii) separate the signals from a large scale of sensors reliably. Our experimental results show that our design can support concurrent tracking of 150 targets with a 12kHz per-tag sampling rate. We also demonstrate with multiple sensing applications that μTag can achieve high-speed and large-scale motion tracking and rotation frequency sensing. The PCB power consumption of μTag is 38 107μW, according to the operating frequency of the tag. Our ASIC simulation based on the 40nm CMOS process shows that the power consumption can be further reduced to 0.13 0.52μW.

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