Deep Learning Techniques for Automatic Modulation Classification: A Systematic Literature Review

dc.contributor.authorAli Ghunaim, Sara
dc.contributor.authorNasir, Qassim
dc.contributor.authorAbu Talib, Manar
dc.date.accessioned2022-06-01T07:36:30Z
dc.date.accessioned2023-08-19T08:18:51Z
dc.date.available2022-06-01T07:36:30Z
dc.date.available2023-08-19T08:18:51Z
dc.date.issued2020-11
dc.description.abstractImplementation of Automatic modulation classification originated in the military field several years ago. Threat analysis, surveillance, and welfare where of great concern, thus this urged the importance to study the application of automatic modulation classification for signal recognition. In this research survey a Systematic Literature Review is conducted to study the implementation of deep learning algorithms in modulation classification. Our survey conducts a study from four perspectives including: deep learning techniques/models, performance metrics used, deep learning models adopted, and types of modulation classification classified.en_US
dc.identifier.citationGhunaim, S. A., Nasir, Q., & Talib, M. A. (2020, November). Deep Learning Techniques for Automatic Modulation Classification: A Systematic Literature Review. In 2020 14th International Conference on Innovations in Information Technology (IIT) (pp. 108-113). IEEE.‏en_US
dc.identifier.doihttps://doi.org/10.1109/IIT50501.2020.9299053
dc.identifier.urihttps://edms.wexl.in/handle/1/3594
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDeep learningen_US
dc.subjectTechnological innovationen_US
dc.subjectModulation Classificationen_US
dc.subjectSignal Intelligenceen_US
dc.subjectArtificial Intelligenceen_US
dc.titleDeep Learning Techniques for Automatic Modulation Classification: A Systematic Literature Reviewen_US
dc.title.alternativeJournal articleen_US
dc.typeArticleen_US

Files

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: