信号(编程语言)
比例(比率)
CMOS芯片
跟踪(教育)
无线电频率
计算机科学
电子工程
功率(物理)
实时计算
工程类
电信
物理
量子力学
心理学
教育学
程序设计语言
作者
M. Xie,Meng Jin,Fengyuan Zhu,Y S Zhang,Xiaohua Tian,Xinbing Wang,Chenghu Zhou
标识
DOI:10.1145/3636534.3649351
摘要
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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