Abdullah Samarkandi, Alhussain Almarhabi, Hatim Alhazmi, Yuan Yao
{"title":"基于深度学习的调制分类组合信号表示:模糊函数、星座图和眼图","authors":"Abdullah Samarkandi, Alhussain Almarhabi, Hatim Alhazmi, Yuan Yao","doi":"10.1109/WOCC58016.2023.10139474","DOIUrl":null,"url":null,"abstract":"We exploit deep learning convolutional neural networks (CNN) based on joint image representation and propose an automatic modulation classification algorithm to classify the communication signals. The combined representations include a constellation diagram, an ambiguity function (AF), and an eye diagram. Experimentation results show that combining constellation and eye diagrams achieves superior classification performance compared to having these representations separately. Combining AF and an eye diagram results in improvement at low SNR.","PeriodicalId":226792,"journal":{"name":"2023 32nd Wireless and Optical Communications Conference (WOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combined Signal Representations for Modulation Classification Using Deep Learning: Ambiguity Function, Constellation Diagram, and Eye Diagram\",\"authors\":\"Abdullah Samarkandi, Alhussain Almarhabi, Hatim Alhazmi, Yuan Yao\",\"doi\":\"10.1109/WOCC58016.2023.10139474\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We exploit deep learning convolutional neural networks (CNN) based on joint image representation and propose an automatic modulation classification algorithm to classify the communication signals. The combined representations include a constellation diagram, an ambiguity function (AF), and an eye diagram. Experimentation results show that combining constellation and eye diagrams achieves superior classification performance compared to having these representations separately. Combining AF and an eye diagram results in improvement at low SNR.\",\"PeriodicalId\":226792,\"journal\":{\"name\":\"2023 32nd Wireless and Optical Communications Conference (WOCC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 32nd Wireless and Optical Communications Conference (WOCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOCC58016.2023.10139474\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 32nd Wireless and Optical Communications Conference (WOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCC58016.2023.10139474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combined Signal Representations for Modulation Classification Using Deep Learning: Ambiguity Function, Constellation Diagram, and Eye Diagram
We exploit deep learning convolutional neural networks (CNN) based on joint image representation and propose an automatic modulation classification algorithm to classify the communication signals. The combined representations include a constellation diagram, an ambiguity function (AF), and an eye diagram. Experimentation results show that combining constellation and eye diagrams achieves superior classification performance compared to having these representations separately. Combining AF and an eye diagram results in improvement at low SNR.