{"title":"宽带传感和盲分层调制分类的USRP N210演示","authors":"M. Laghate, S. Chaudhari, D. Cabric","doi":"10.1109/DySPAN.2017.7920748","DOIUrl":null,"url":null,"abstract":"Blind modulation classification problem is particularly difficult when the exact frequency band of the signal is unknown since the modulation classifiers require accurate estimates of the signal parameters such as center frequency, bandwidth, and SNR. In this work, we demonstrate a hierarchical classification tree that filters and classifies a received signal as AM, FM, 4/16/64-QAM, 2/4/8-PAM, 4/8/16-PSK, DSSS, and FSK. Coarse estimates of signal parameters are obtained from energy detection and are refined using cyclostationary estimators. Cumulants and cyclostationarity are used to classify AM and FM while a reduced complexity Kuiper test is used for differentiating modulation level for QAM, PAM, and PSK. The effects of multipath are countered using a blind equalizer. The classifier is implemented in C++ using GNURadio libraries and is demonstrated using a USRP N210.","PeriodicalId":221877,"journal":{"name":"2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"USRP N210 demonstration of wideband sensing and blind hierarchical modulation classification\",\"authors\":\"M. Laghate, S. Chaudhari, D. Cabric\",\"doi\":\"10.1109/DySPAN.2017.7920748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Blind modulation classification problem is particularly difficult when the exact frequency band of the signal is unknown since the modulation classifiers require accurate estimates of the signal parameters such as center frequency, bandwidth, and SNR. In this work, we demonstrate a hierarchical classification tree that filters and classifies a received signal as AM, FM, 4/16/64-QAM, 2/4/8-PAM, 4/8/16-PSK, DSSS, and FSK. Coarse estimates of signal parameters are obtained from energy detection and are refined using cyclostationary estimators. Cumulants and cyclostationarity are used to classify AM and FM while a reduced complexity Kuiper test is used for differentiating modulation level for QAM, PAM, and PSK. The effects of multipath are countered using a blind equalizer. The classifier is implemented in C++ using GNURadio libraries and is demonstrated using a USRP N210.\",\"PeriodicalId\":221877,\"journal\":{\"name\":\"2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)\",\"volume\":\"113 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DySPAN.2017.7920748\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DySPAN.2017.7920748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
USRP N210 demonstration of wideband sensing and blind hierarchical modulation classification
Blind modulation classification problem is particularly difficult when the exact frequency band of the signal is unknown since the modulation classifiers require accurate estimates of the signal parameters such as center frequency, bandwidth, and SNR. In this work, we demonstrate a hierarchical classification tree that filters and classifies a received signal as AM, FM, 4/16/64-QAM, 2/4/8-PAM, 4/8/16-PSK, DSSS, and FSK. Coarse estimates of signal parameters are obtained from energy detection and are refined using cyclostationary estimators. Cumulants and cyclostationarity are used to classify AM and FM while a reduced complexity Kuiper test is used for differentiating modulation level for QAM, PAM, and PSK. The effects of multipath are countered using a blind equalizer. The classifier is implemented in C++ using GNURadio libraries and is demonstrated using a USRP N210.