A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning
Underwater acoustic channels, influenced by time-varying, space-varying, frequency-varying, and multipath effects, pose significant interference challenges to underwater acoustic communication (UWAC) signals, especially in non-cooperative scenarios. The task of modulating and identifying distorted s...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/11/8/1632 |
| _version_ | 1797584187986804736 |
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| author | Run Zhang Chengbing He Lianyou Jing Chaopeng Zhou Chao Long Jiachao Li |
| author_facet | Run Zhang Chengbing He Lianyou Jing Chaopeng Zhou Chao Long Jiachao Li |
| author_sort | Run Zhang |
| collection | DOAJ |
| description | Underwater acoustic channels, influenced by time-varying, space-varying, frequency-varying, and multipath effects, pose significant interference challenges to underwater acoustic communication (UWAC) signals, especially in non-cooperative scenarios. The task of modulating and identifying distorted signals faces huge challenges. Although traditional modulation recognition methods can be useful in the radio field, they often prove inadequate in underwater environments. This paper introduces a modulation recognition system for recognizing UWAC signals based on higher-order cumulants and deep learning. The system achieves blind recognition of received UWAC signals even under non-cooperative conditions. Higher-order cumulants are employed due to their excellent noise resistance, enabling the differentiation of OFDM signals from PSK and FSK signals. Additionally, the high-order spectra differences among signals are utilized for the intra-class recognition of PSK and FSK signals. Both simulation and lake test results substantiate the effectiveness of the proposed method. |
| first_indexed | 2024-03-10T23:49:31Z |
| format | Article |
| id | doaj.art-750367f601f14c5fa1a74cf9bad0886a |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T23:49:31Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-750367f601f14c5fa1a74cf9bad0886a2023-11-19T01:46:53ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-08-01118163210.3390/jmse11081632A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep LearningRun Zhang0Chengbing He1Lianyou Jing2Chaopeng Zhou3Chao Long4Jiachao Li5School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaResearch and Development Institute, Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, ChinaUnderwater acoustic channels, influenced by time-varying, space-varying, frequency-varying, and multipath effects, pose significant interference challenges to underwater acoustic communication (UWAC) signals, especially in non-cooperative scenarios. The task of modulating and identifying distorted signals faces huge challenges. Although traditional modulation recognition methods can be useful in the radio field, they often prove inadequate in underwater environments. This paper introduces a modulation recognition system for recognizing UWAC signals based on higher-order cumulants and deep learning. The system achieves blind recognition of received UWAC signals even under non-cooperative conditions. Higher-order cumulants are employed due to their excellent noise resistance, enabling the differentiation of OFDM signals from PSK and FSK signals. Additionally, the high-order spectra differences among signals are utilized for the intra-class recognition of PSK and FSK signals. Both simulation and lake test results substantiate the effectiveness of the proposed method.https://www.mdpi.com/2077-1312/11/8/1632underwater acoustic communicationmodulation recognitionhigher-order cumulantsdeep learning |
| spellingShingle | Run Zhang Chengbing He Lianyou Jing Chaopeng Zhou Chao Long Jiachao Li A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning Journal of Marine Science and Engineering underwater acoustic communication modulation recognition higher-order cumulants deep learning |
| title | A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning |
| title_full | A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning |
| title_fullStr | A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning |
| title_full_unstemmed | A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning |
| title_short | A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning |
| title_sort | modulation recognition system for underwater acoustic communication signals based on higher order cumulants and deep learning |
| topic | underwater acoustic communication modulation recognition higher-order cumulants deep learning |
| url | https://www.mdpi.com/2077-1312/11/8/1632 |
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