@inproceedings{660cf111c5e74b84aeb281bd730c928a,
title = "On Noise-Sensitivity of Unlimited Sampling in Line Spectral Estimation",
abstract = "The unlimited sampling framework, utilizing modulo analog-to-digital converters (ADCs), has recently been introduced to mitigate the information loss caused by the dynamic range limitations of traditional ADCs. In this paper, we evaluate the noise sensitivity of unlimited sampling in line spectral estimation by deriving the Cram{\'e}r-Rao bound (CRB) and show that estimation based solely the modulo measurements can be sensitive to noise. To address this issue, we propose integrating the modulo ADC-based unlimited sampling with the sign information of the original signal. We compare the CRBs of different unlimited sampling frameworks and show the benefit of enhanced robustness to noise by the sign-aided approach.",
keywords = "Cram{\'e}r-Rao bound, Line spectral estimation, modulo ADC, noise sensitivity, sign information, unlimited sampling",
author = "Wenlong Wang and Zai Yang",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 ; Conference date: 06-04-2025 Through 11-04-2025",
year = "2025",
doi = "10.1109/ICASSP49660.2025.10889380",
language = "英语",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Rao, \{Bhaskar D\} and Isabel Trancoso and Gaurav Sharma and Mehta, \{Neelesh B.\}",
booktitle = "2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 - Proceedings",
}