Deep neural network-based blind modulation classification for fading channels
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Junghwan | - |
dc.contributor.author | Kim, Byeoungdo | - |
dc.contributor.author | Kim, Jaekyum | - |
dc.contributor.author | Yoon, Dongweon | - |
dc.contributor.author | Choi, Jun Won | - |
dc.date.accessioned | 2021-08-02T14:26:16Z | - |
dc.date.available | 2021-08-02T14:26:16Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2017-12 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/18564 | - |
dc.description.abstract | In this paper, we propose high performance blind modulation classification (BMC) technique based on deep neural network (DNN) for fading channels. First, we provide the large and diverse set of the features that exhibit statistical relevance to modulation class in fading channels. Then, we use those features to train the DNN to classify the modulation class. Owing to the capability of DNN to learn the complex structure in high dimensional feature space, the proposed scheme achieves the excellent classification accuracy using a number of features in challenging fading environments. Numerical evaluation demonstrates the superiority of the proposed technique over the existing BMC methods. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Deep neural network-based blind modulation classification for fading channels | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Yoon, Dongweon | - |
dc.contributor.affiliatedAuthor | Choi, Jun Won | - |
dc.identifier.doi | 10.1109/ICTC.2017.8191038 | - |
dc.identifier.scopusid | 2-s2.0-85046891389 | - |
dc.identifier.bibliographicCitation | International Conference on Information and Communication Technology Convergence: ICT Convergence Technologies Leading the Fourth Industrial Revolution, ICTC 2017, v.2017-December, pp.551 - 554 | - |
dc.relation.isPartOf | International Conference on Information and Communication Technology Convergence: ICT Convergence Technologies Leading the Fourth Industrial Revolution, ICTC 2017 | - |
dc.citation.title | International Conference on Information and Communication Technology Convergence: ICT Convergence Technologies Leading the Fourth Industrial Revolution, ICTC 2017 | - |
dc.citation.volume | 2017-December | - |
dc.citation.startPage | 551 | - |
dc.citation.endPage | 554 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Classification (of information) | - |
dc.subject.keywordPlus | Fading channels | - |
dc.subject.keywordPlus | Feature extraction | - |
dc.subject.keywordPlus | Modulation | - |
dc.subject.keywordPlus | Numerical methods | - |
dc.subject.keywordPlus | Blind modulation classifications | - |
dc.subject.keywordPlus | Classification accuracy | - |
dc.subject.keywordPlus | Complex structure | - |
dc.subject.keywordPlus | Cumulants | - |
dc.subject.keywordPlus | Fading environment | - |
dc.subject.keywordPlus | High-dimensional feature space | - |
dc.subject.keywordPlus | Statistical features | - |
dc.subject.keywordPlus | Deep neural networks | - |
dc.subject.keywordAuthor | Blind modulation classification | - |
dc.subject.keywordAuthor | Cumulant | - |
dc.subject.keywordAuthor | Deep neural network | - |
dc.subject.keywordAuthor | Feature selection | - |
dc.subject.keywordAuthor | Statistical feature | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8191038 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.