基于非二进制分割电容的双旁路窗口的9.68 nW 57.51dB SNDR SAR ADC。

Kangkang Sun, Jingjing Liu, Feng Yan, Haoning Sun, Yafei Zhang, Yuan Ren, Linfei Huang, Yao Pi, Wanqing Wu, Jian Guan
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引用次数: 0

摘要

提出了一种基于非二进制分割电容的低功耗逐次逼近寄存器(SAR)双旁路窗口模数转换(ADC)。为了降低功耗,由分路电容构成的旁路窗口可以最大限度地覆盖静息状态和激发态的生物信号。当信号落在指定的窗口内时,跳过不必要的转换周期。该过程主要由数字电路判断和控制,鲁棒性强,不需要校准。同时,提出了一种低功耗动态CMOS比较器,该比较器可以有效地减小锁存节点在比较器工作过程中的电压变化,进一步降低功耗。基于180nm工艺的SAR ADC,在0.6V电源电压下的功耗为9.68nW,采样率为5.21kS/s。信噪比(SNDR)和无杂散动态范围(SFDR)分别为57.51dB和71.68dB。它还实现了9.26位的有效位数(ENOB)和2.9 fJ/con . step的瓦尔登品质系数(FoM)。所提出的SAR ADC也通过收集到的肌电图(EMG)、心电图(ECG)和脑电图(EEG)信号进行验证。量化肌电信号的平均功耗为7.95 nW,为生物医学应用中的低功耗SAR adc提供了一个有吸引力的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 9.68 nW 57.51dB SNDR SAR ADC with Dual Bypass Windows Based on Non-binary Split Capacitors for Biomedical Applications.

The paper proposes a low-power Successive Approximation Register (SAR) Analog-to-Digital Conversion (ADC) with dual bypass windows based on non-binary split capacitors. To reduce the power consumption, the bypass windows constituted by the split capacitors can maximize the coverage of biological signals both in the resting state and excited state. When the signal falls within the designated window, unnecessary conversion cycles are skipped. This process is mainly judged and controlled by digital circuits, which is highly robust and does not require calibration. Meanwhile, a low-power dynamic CMOS comparator is proposed, which can effectively reduce the voltage variation of the latch node during the comparator's operation, further reducing power consumption. The proposed SAR ADC, based on a 180nm process, measures a power consumption of 9.68nW at a supply voltage of 0.6V and a sampling rate of 5.21kS/s. The signal-to-noise-and-distortion ratio (SNDR) and the spur-free dynamic range (SFDR) are measured at 57.51dB and 71.68dB, respectively. It also achieves an effective number of bits (ENOB) of 9.26 bits and a Walden figure-of-merit (FoM) of 2.9 fJ/conv.-step. The proposed SAR ADC is also verified by collected electromyogram (EMG), electrocardiogram (ECG), and electroencephalogram (EEG) signals. The average power consumption for quantifying EMG signals is 7.95 nW, providing an attractive solution for low-power SAR ADCs in biomedical applications.

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