Achieving Robustness in Blind Modulo Analog-to-Digital Conversion

TL;DR

This paper introduces a robust modulo-ADC system that overcomes prediction error limitations, ensuring stable digitization of complex signals with improved noise reduction, demonstrated through simulation results.

Contribution

We propose an enhanced modulo-unfolding algorithm with a reliable detector that maintains stability without assuming bounded prediction errors.

Findings

The new method outperforms previous approaches in stability and accuracy.

Simulation results show significant noise reduction and robustness.

The approach extends the applicability of modulo-ADC in practical scenarios.

Abstract

The need to digitize signals with intricate spectral characteristics often challenges traditional analog-to-digital converters (ADCs). The recently proposed modulo-ADC architecture offers a promising alternative by leveraging inherent features of the input signals. This approach can dramatically reduce the number of bits required for the conversion while maintaining the desired fidelity. However, the core algorithm of this architecture, which utilizes a prediction filter, functions properly only when the respective prediction error is bounded. In practice, this assumption may not always hold, leading to considerable instability and performance degradation. To address this limitation, we propose an enhanced modulo-unfolding solution without this assumption. We develop a reliable detector to successfully unfold the signals, yielding a robust solution. Consequently, the reinforced system maintains proper operation in scenarios where the original approach fails, while also reducing the quantization noise. We present simulation results that demonstrate the superior performance of our approach in a representative setting.