A Novel Event-Based Method for ASK Demodulation

Alexis Rodrigo Iga Jadue, S. Engels, L. Fesquet
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Abstract

This paper presents a novel ASK demodulation technique, using an Event-Based ADC (EB-ADC) and a digital ASK demodulation algorithm. The EB-ADC employs a minimalist Level Crossing Sample Scheme (LCSS) with only 2 levels, and uses a Time-to-Digital Converter (TDC) for measuring the time elapsed between two consecutive level crossings (events). The level crossing detection modules are composed of two strong-arm comparators. These comparators were characterized through an electrical simulation and then modeled in SystemVerilog in order to be integrated in a full digital simulation environment. The RF input signal of the testbench and its noise model have been modeled by replicating python's awgn function of commpy library. This demodulation technique takes advantage of the time measurement elapsed between two adjacent events, to apply a digital demodulation algorithm, for improving the symbol recognition performance and the noise resiliency, reaching for example a $\text{BER}=3.33\cdot 10^{-7}$ with a modulation index of 10%, a bit rate of 6.78 Mbps and a SNR of 16 dB. A circuit implementing this approach is currently in fabrication in FDSOI 28nm STMicroelectronics technology.
一种基于事件的ASK解调方法
本文提出了一种新的ASK解调技术,使用基于事件的ADC (EB-ADC)和数字ASK解调算法。EB-ADC采用极简的电平交叉采样方案(LCSS),只有2个电平,并使用时间-数字转换器(TDC)来测量两个连续的电平交叉(事件)之间经过的时间。水平交叉检测模块由两个强臂比较器组成。这些比较器通过电气仿真进行表征,然后在SystemVerilog中建模,以便集成在全数字仿真环境中。通过复制compy库中的python awgn函数,对试验台的射频输入信号及其噪声模型进行了建模。这种解调技术利用两个相邻事件之间的测量时间,应用数字解调算法,以提高符号识别性能和噪声弹性,例如达到$\text{BER}=3.33\cdot 10^{-7}$,调制指数为10%,比特率为6.78 Mbps,信噪比为16 dB。实现这种方法的电路目前正在FDSOI 28nm意法半导体技术中制造。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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