A Low-Power Edge Detection Technique for Sensor Wake-Up Applications

Author:

Wang Yao1,Wang Haibo2,Wen Guangjun1

Affiliation:

1. Center for RFIC and System Technology, School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China

2. Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, Illinois 62901, USA

Abstract

A novel low-power edge detection circuit is presented in this work. Upon the arrival of signal falling edge, the proposed design establishes a small voltage difference between the gate and source terminals of a MOS transistor which slightly increases the MOS transistor leakage current. A current integration-based approach is used to robustly sense the current change and subsequently detect the signal falling edge. The design is suitable for ultra-low-power sensor wake-up circuits. Design guidelines for achieving optimal detection sensitivity as well as the implementation of calibration circuits for coping with process variations and mismatches are discussed in the paper. Simulation results are presented to demonstrate the performance of the proposed circuit.

Publisher

World Scientific Pub Co Pte Lt

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Electrical and Electronic Engineering,Hardware and Architecture

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An overview on low energy wake-up radio technology: Active and passive circuits associated with MAC and routing protocols;Journal of Network and Computer Applications;2021-09

2. Edge Detection Based on Fuzzy Logic and Hybrid Types of Shannon Entropy;Journal of Circuits, Systems and Computers;2020-03-20

3. Differential input area efficient current comparator;PHYSICS, TECHNOLOGIES AND INNOVATION (PTI-2019): Proceedings of the VI International Young Researchers’ Conference;2019

4. Ultra Low Power Wake-Up Radios: A Hardware and Networking Survey;IEEE Communications Surveys & Tutorials;2017

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