安徽大学学报(自然科学版)2025,Vol.49Issue(1) :61-69.DOI:10.3969/j.issn.1000-2162.2025.01.008

一种具有低调制深度和低功耗的自适应抗噪超高频RFID解调器设计

Adaptive noise-resistant UHF RFID demodulator design with low modulation depth and low power consumption

王翊 陈冲 许耀华 柏娜
安徽大学学报(自然科学版)2025,Vol.49Issue(1) :61-69.DOI:10.3969/j.issn.1000-2162.2025.01.008

一种具有低调制深度和低功耗的自适应抗噪超高频RFID解调器设计

Adaptive noise-resistant UHF RFID demodulator design with low modulation depth and low power consumption

王翊 1陈冲 1许耀华 1柏娜1
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作者信息

  • 1. 安徽大学集成电路学院,安徽 合肥 230601
  • 折叠

摘要

超高频射频识别技术(radio frequency identification,简称RFID)是目前RFID发展的主流,但是传统的RFID幅度调制(amplitude shift keying,简称ASK)解调器在应对低调制深度的射频输入信号时难以实现精准解调.针对这种情况,该文基于GJB7377.1B标准系统的超高频RFID ASK解调器,设计了一个由包络检测、低通滤波、放大器和比较器组成的低功耗、自适应抗噪ASK解调器.与传统的RFID ASK解调器相比,使用了迟滞放大器来实现低调制深度下的精准解调,使用了偏置电路来降低功耗,并使用了迟滞单元来抗噪.经过测试和验证,该RFID ASK解调器可以在2.31%的最小调制深度下解调信号,其功耗仅为421.63 nW,且在射频信号(radio frequency,简称RF)加入噪声的情况下也能实现精准解调.

Abstract

UHF radio frequency identification technology(RFID)is currently the mainstream of RFID development,but the traditional RFID amplitude shift keying(ASK)demodulator in response to the low modulation depth of the RF input signal is difficult to achieve accurate demodulation work.For this situation this paper based on the GJB7377.1B standard system of UHF RFID ASK demodulator,designed low power,adaptive noise ASK demodulator which composed of the envelope detection,low-pass filtering,amplifier and comparator.Compared with conventional RFID ASK demodulators,hysteresis amplifiers were used to achieve accurate demodulation at low modulation depths,bias circuits were used to reduce power consumption,and hysteresis units were used for noise immunity.The RFID ASK demodulator had been tested and verified to demodulate signals at a minimum modulation depth of 2.31%,with a demodulator power consumption of only 421.63 nW,and achieved accurate demodulation even when noise was added to the radio frequency(RF)signal.

关键词

低调制深度/低功率/自适应抗噪/超高频射频识别技术

Key words

low modulation depth/low power/adaptive noise-resistant/UHF radio frequency identification technology

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出版年

2025
安徽大学学报(自然科学版)
安徽大学

安徽大学学报(自然科学版)

北大核心
影响因子:0.49
ISSN:1000-2162
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