Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/32051
Title: | Line spectral estimation with unlimited sensing |
Authors: | Wang, H Fang, J Li, H Leus, G Zhu, R Gan, L |
Keywords: | unlimited sensing;line spectral estimation;modulo samples |
Issue Date: | 23-Jul-2025 |
Publisher: | Elsevier |
Citation: | Wang, H. et al. (2026) 'Line spectral estimation with unlimited sensing', Signal Processing, 238, 110205, pp. 1 - 15. doi: 10.1016/j.sigpro.2025.110205. |
Abstract: | In the paper, we consider the line spectral estimation problem in an unlimited sensing framework (USF), where a modulo analog-to-digital converter (ADC) is employed to fold the input signal back into a bounded interval before quantization. Such an operation is mathematically equivalent to taking the modulo of the input signal with respect to the interval. To overcome the noise sensitivity of higher-order difference-based methods, we explore the properties of the first-order difference of modulo samples, and develop two line spectral estimation algorithms based on the first-order difference, which are robust against noise. Specifically, we show that, with a high probability, the first-order difference of the original samples is equivalent to that of the modulo samples. By utilizing this property, line spectral estimation is solved via a robust sparse signal recovery approach. The second algorithms is built on our finding that, with a sufficiently high sampling rate, the first-order difference of the original samples can be decomposed as a sum of the first-order difference of the modulo samples and a sequence whose elements are confined to three possible values. This decomposition enables us to formulate the line spectral estimation problem as a mixed integer linear program that can be efficiently solved. Simulation results show that both proposed methods are robust against noise and achieve a significant performance improvement over the higher-order difference-based method. methods. |
Description: | Data availability: Data will be made available on request. |
URI: | https://bura.brunel.ac.uk/handle/2438/32051 |
DOI: | https://doi.org/10.1016/j.sigpro.2025.110205 |
ISSN: | 0165-1684 |
Other Identifiers: | ORCiD: Hongwei Wang https://orcid.org/0000-0002-3385-7284 ORCiD: Ruixiang Zhu https://orcid.org/0009-0006-7298-1401 ORCiD: Lu Gan https://orcid.org/0000-0003-1056-7660 Article number: 110205 |
Appears in Collections: | Dept of Electronic and Electrical Engineering Embargoed Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | Copyright © 2025 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ (see: https://www.elsevier.com/about/policies/sharing ). | 1.12 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License