Accurate Automatic Extraction of Signal Components From Noisy Radio Spectrograms

Lopez-Benitez, Miguel ORCID: 0000-0003-0526-6687 and Alammar, Mohammed M ORCID: 0000-0002-4925-5472 (2022) Accurate Automatic Extraction of Signal Components From Noisy Radio Spectrograms. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 8 (4). pp. 1604-1617.

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Official URL: http://dx.doi.org/10.1109/tccn.2022.3205689

Abstract

In some radio communication scenarios it is useful to extract the bandwidth and start/end times of each transmission in a spectrogram. However, few methods in the literature are able to extract this information without human manual intervention, and the few existing ones have a limited accuracy. In this context, this work overcomes these limitations by proposing a novel fully automated method that can provide this information with high accuracy. The results obtained from simulations and hardware experiments show that the proposed method outperforms other methods available in the literature, achieving a virtually perfect accuracy for signal-to-noise ratio values as low as -10 dB.

Item Type:	Article
Uncontrolled Keywords:	clustering algorithms, signal area estimation, spectrum awareness, autonomous wireless systems, Spectrogram
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	05 Sep 2022 07:26
Last Modified:	15 Mar 2024 06:08
DOI:	10.1109/TCCN.2022.3205689
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3163401