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Electrical Engineering and Systems Science > Signal Processing

arXiv:1909.02515 (eess)
[Submitted on 5 Sep 2019 ]

Title: Dual Frequency Comb Assisted Analog-to-Digital Conversion of Subcarrier Modulated Signals

Title: 双频率梳辅助的次载波调制信号模数转换

Authors:Callum Deakin, Zhixin Liu
Abstract: Photonic analog to digital conversion offers promise to overcome the signal-to-noise ratio (SNR) and sample rate trade-off in conventional analog to digital converters (ADCs), critical for modern digital communications and signal analysis. We propose using phase-stable dual frequency combs with a fixed frequency spacing offset to downconvert spectral slices of a broadband signal and enable high resolution parallel digitization. To prove the concept of our proposed method, we demonstrate the detection of a 10-GHz subcarrier modulated (SCM) signal using 500-MHz bandwidth ADCs by optically converting the SCM signal to ten 1-GHz bandwidth signals that can be processed in parallel for full signal detection and reconstruction. Using sinusoidal wave based standard ADC testing, we demonstrate a spurious-free dynamic range (SFDR) of >45dB and signal-to-noise-and-distortion (SINAD) of >20dB, only limited by the receiver front-end design. Our experimental investigation reveals that this SINAD limitation can be overcome by improved receiver design, promising high resolution ADC for broadband signals.
Abstract: 光子模数转换有望克服传统模数转换器(ADC)中的信噪比(SNR)和采样率之间的权衡问题,这对现代数字通信和信号分析至关重要。 我们提出使用具有固定频率偏移的相位稳定双频梳来下变频宽带信号的光谱切片,并实现高分辨率的并行数字化。 为了验证我们所提出方法的概念,我们通过光学转换10-GHz副载波调制(SCM)信号为十个1-GHz带宽信号,利用500-MHz带宽ADC并行处理以实现完整信号检测和重建,从而演示了SCM信号的检测。 使用基于正弦波的标准ADC测试,我们展示了大于45 dB的无杂散动态范围(SFDR)和大于20 dB的信噪失真比(SINAD),这一限制仅由接收机前端设计决定。 我们的实验研究表明,通过改进的接收机设计可以克服这一SINAD限制,为宽带信号提供高分辨率ADC,前景可期。
Subjects: Signal Processing (eess.SP) ; Optics (physics.optics)
Cite as: arXiv:1909.02515 [eess.SP]
  (or arXiv:1909.02515v1 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.1909.02515
arXiv-issued DOI via DataCite

Submission history

From: Callum Deakin [view email]
[v1] Thu, 5 Sep 2019 16:35:43 UTC (388 KB)
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