{"title":"基于变压器的非合作无线电通信关系识别","authors":"Dejun He, Xinrong Wu, Lu Yu, Tianchi Wang","doi":"10.1145/3571662.3571688","DOIUrl":null,"url":null,"abstract":"The recognition of communication relationships under Non-cooperative conditions is significant for understanding the network composition of unknown targets, inferring network topology, and identifying key nodes, which is a prerequisite and basis for conducting efficient electronic countermeasures. However, under Non-cooperative conditions, for prior knowledge related to the target network is difficult to obtain, the communication relationships recognition faces enormous challenges. To address this issue, we construct a system model, analyze the mechanism of wireless communication interaction, extract feature series of signals from spectrum monitoring data, and propose a Transformer-based algorithm for recognizing target network communication relationships. This paper conducts simulation experiments in different scenarios to compare the Transformer-based communication relation recognition algorithm with the other four methods, such as SVM, CNN-based recognition algorithm, ResNet-based recognition algorithm, and LSTM-based recognition algorithm, respectively. And results demonstrate that the proposed algorithm shows high recognition accuracy, good anti-interference performance, and robustness.","PeriodicalId":235407,"journal":{"name":"Proceedings of the 8th International Conference on Communication and Information Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recognition of Non-cooperative Radio Communication Relationships Based on Transformer\",\"authors\":\"Dejun He, Xinrong Wu, Lu Yu, Tianchi Wang\",\"doi\":\"10.1145/3571662.3571688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recognition of communication relationships under Non-cooperative conditions is significant for understanding the network composition of unknown targets, inferring network topology, and identifying key nodes, which is a prerequisite and basis for conducting efficient electronic countermeasures. However, under Non-cooperative conditions, for prior knowledge related to the target network is difficult to obtain, the communication relationships recognition faces enormous challenges. To address this issue, we construct a system model, analyze the mechanism of wireless communication interaction, extract feature series of signals from spectrum monitoring data, and propose a Transformer-based algorithm for recognizing target network communication relationships. This paper conducts simulation experiments in different scenarios to compare the Transformer-based communication relation recognition algorithm with the other four methods, such as SVM, CNN-based recognition algorithm, ResNet-based recognition algorithm, and LSTM-based recognition algorithm, respectively. And results demonstrate that the proposed algorithm shows high recognition accuracy, good anti-interference performance, and robustness.\",\"PeriodicalId\":235407,\"journal\":{\"name\":\"Proceedings of the 8th International Conference on Communication and Information Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th International Conference on Communication and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3571662.3571688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th International Conference on Communication and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3571662.3571688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of Non-cooperative Radio Communication Relationships Based on Transformer
The recognition of communication relationships under Non-cooperative conditions is significant for understanding the network composition of unknown targets, inferring network topology, and identifying key nodes, which is a prerequisite and basis for conducting efficient electronic countermeasures. However, under Non-cooperative conditions, for prior knowledge related to the target network is difficult to obtain, the communication relationships recognition faces enormous challenges. To address this issue, we construct a system model, analyze the mechanism of wireless communication interaction, extract feature series of signals from spectrum monitoring data, and propose a Transformer-based algorithm for recognizing target network communication relationships. This paper conducts simulation experiments in different scenarios to compare the Transformer-based communication relation recognition algorithm with the other four methods, such as SVM, CNN-based recognition algorithm, ResNet-based recognition algorithm, and LSTM-based recognition algorithm, respectively. And results demonstrate that the proposed algorithm shows high recognition accuracy, good anti-interference performance, and robustness.