mlsanityData to 14 Oct 2026

Modulo Sampling: Performance Guarantees in The Presence of Quantization

arXiv 2501.01506 ↗First posted 2 Jan 2025eess.SPcited by 1

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Abstract (arXiv)

In this paper, we investigate the relationship between the dynamic range and quantization noise power in modulo analog-to-digital converters (ADCs). Two modulo ADC systems are considered: (1) a modulo ADC which outputs the folded samples and an additional 1-bit folding information signal, and (2) a modulo ADC without the 1-bit information. A recovery algorithm that unfolds the quantized modulo samples using the extra 1-bit folding information is analyzed. Using the dithered quantization framework, we show that an oversampling factor of OF > 3 and a quantizer resolution of b > 3 are sufficient conditions to unfold the modulo samples. When these conditions are met, we demonstrate that the mean squared error (MSE) performance of modulo ADC with an extra 1-bit folding information signal is better than that of a conventional ADC with the same number of bits used for amplitude quantization. Since folding information is typically not available in modulo ADCs, we also propose and analyze a recovery algorithm based on orthogonal matching pursuit (OMP) that does not require the 1-bit folding information. In this case, we prove that OF > 3 and b > 3 + log2(δ) for some δ > 1 are sufficient conditions to unfold the modulo samples. For the two systems considered, we show that, with sufficient number of bits for amplitude quantization, the mean squared error (MSE) of a modulo ADC is Oleft(frac1OF3right) whereas that of a conventional ADC is only Oleft(frac1OFright). We extend the analysis to the case of simultaneous acquisition of weak and strong signals occupying different frequency bands. Finally, numerical results are presented to validate the derived performance guarantees.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 59 references that are in the map. First posted on arXiv 2 Jan 2025.

Builds on

17 of 59 references.

References · 17

  1. 2019On Unlimited Sampling and Reconstructioncited by 22
  2. 2021Unlimited Sampling from Theory to Practice: Fourier-Prony Recovery and Prototype ADCcited by 17
  3. 2022UNO: Unlimited Sampling Meets One-Bit Quantizationcited by 11
  4. 2019Above the Nyquist Rate, Modulo Folding Does Not Hurtcited by 9
  5. 2022Back in the US-SR: Unlimited Sampling and Sparse Super-Resolution with its Hardware Validationcited by 7
  6. 2018Generalized Approximate Message Passing for Unlimited Sampling of Sparse Signalscited by 6
  7. 2021Residual Recovery Algorithm For Modulo Samplingcited by 6
  8. 2021The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experimentscited by 5
  9. 2022Modulo Sampling of FRI Signalscited by 5
  10. 2022Line Spectral Estimation via Unlimited Samplingcited by 4
  11. 2019Unlimited Dynamic Range Analog-to-Digital Conversioncited by 3
  12. 2023On Hybrid Radar Fusion for Integrated Sensing and Communicationcited by 2
5 more
  1. 2024Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Samplingcited by 2
  2. 2023On the Identifiability from Modulo Measurements under DFT Sensing Matrixcited by 1
  3. 2024Short-time Fourier Transform-based Signal Recovery for Modulo Analog-to-Digital Converterscited by 1
  4. 2024A Modulo Sampling Hardware Prototype and Reconstruction Algorithm Evaluationcited by 1
  5. 2024Low Dynamic Range for RIS-aided Bistatic Integrated Sensing and Communicationcited by 1

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Citing papers per year: 2025: 1.

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  1. 2023Modulation For Modulo: A Sampling-Efficient High-Dynamic Range ADC ↗
  2. 2025Practical Modulo Sampling: Mitigating High-Frequency Components
  3. 2024Achieving Robustness in Blind Modulo Analog-to-Digital Conversion ↗
  4. 2026Lattice Modulo Sampling
  5. 2024Unleashing Dynamic Range and Resolution in Unlimited Sensing Framework via Novel Hardware
  6. 20251-Bit Unlimited Sampling Beyond Fourier Domain: Low-Resolution Sampling of Quantization Noise
  7. 2026Fold First, Detect Directly: Communication Symbol Detection Without Unfolding for Low-Bitrate Modulo-ADCs
  8. 2025Design and Implementation of Parametrized Look-Up Tables for Post-Correction of Oversampling Low-Resolution ADCs