# Unlimited Dynamic Range Analog-to-Digital Conversion

arXiv: https://arxiv.org/abs/1911.09371 · HTML: https://mlsanity.com/paper/1911.09371/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2019.

## Built on by (most cited first, 3 of 3)

- [Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling](https://mlsanity.com/paper/2412.12724/) (2024)
- [Modulo Sampling: Performance Guarantees in The Presence of Quantization](https://mlsanity.com/paper/2501.01506/) (2025)
- [mSQUID: Model-Based Leanred Modulo Recovery at Low Sampling Rates](https://mlsanity.com/paper/2510.18729/) (2025)

## Abstract (arXiv)

Analog-to-digital converters (ADCs) provide the link between continuous-time signals and their discrete-time counterparts, and the Shannon-Nyquist sampling theorem provides the mathematical foundation. Real-world signals have a variable amplitude range, whereas ADCs, by design, have a limited input dynamic range, which results in out-of-range signals getting clipped. In this paper, we propose an unlimited dynamic range ADC (UDR-ADC) that is based on the modulo operation (self-reset feature) to alleviate the problem of clipping. The self-reset feature allows for wrapping of the input amplitudes, which preserves the input dynamic range. We present the signal model and a reconstruction technique to recover the original signal samples from the modulo measurements. We validate the operation of the proposed ADC using circuit simulations in 65 nm complementary metal-oxide-semiconductor (CMOS) process technology. The validation is supplemented by a hardware prototype designed using discrete components. A performance assessment in terms of area, power requirement, and the signal-to-quantization-noise ratio (SQNR) shows that the UDR-ADC outperforms the standard ones.