{"title":"极低信噪比下不同步OFDM信号的多窗频谱检测","authors":"Cong Wang, Xianbin Wang, Hao Li, P. Ho","doi":"10.1109/GLOCOM.2009.5425957","DOIUrl":null,"url":null,"abstract":"Reliable spectrum sensing in low signal-to-noise ratio (SNR) condition is one of the major technical challenges in cognitive radio network. In this paper, we propose a robust spectrum sensing algorithm for unsynchronized low SNR OFDM signal by mitigating the impacts of time and frequency offsets with multiple processing time window and sliding frequency correlator, respectively. In addition, considering that the noise's statistics are unknown to the devices and varying over time, our proposed algorithm is based on a ratio threshold and hence it is not sensitive to the noise power level. Our theoretical and simulation results show that this algorithm works effectively at very low SNR, while being insensitive to time and frequency offsets, and requires no information of the noise's statistics.","PeriodicalId":405624,"journal":{"name":"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Multi-Window Spectrum Sensing of Unsynchronized OFDM Signal at Very Low SNR\",\"authors\":\"Cong Wang, Xianbin Wang, Hao Li, P. Ho\",\"doi\":\"10.1109/GLOCOM.2009.5425957\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reliable spectrum sensing in low signal-to-noise ratio (SNR) condition is one of the major technical challenges in cognitive radio network. In this paper, we propose a robust spectrum sensing algorithm for unsynchronized low SNR OFDM signal by mitigating the impacts of time and frequency offsets with multiple processing time window and sliding frequency correlator, respectively. In addition, considering that the noise's statistics are unknown to the devices and varying over time, our proposed algorithm is based on a ratio threshold and hence it is not sensitive to the noise power level. Our theoretical and simulation results show that this algorithm works effectively at very low SNR, while being insensitive to time and frequency offsets, and requires no information of the noise's statistics.\",\"PeriodicalId\":405624,\"journal\":{\"name\":\"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOCOM.2009.5425957\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2009.5425957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Window Spectrum Sensing of Unsynchronized OFDM Signal at Very Low SNR
Reliable spectrum sensing in low signal-to-noise ratio (SNR) condition is one of the major technical challenges in cognitive radio network. In this paper, we propose a robust spectrum sensing algorithm for unsynchronized low SNR OFDM signal by mitigating the impacts of time and frequency offsets with multiple processing time window and sliding frequency correlator, respectively. In addition, considering that the noise's statistics are unknown to the devices and varying over time, our proposed algorithm is based on a ratio threshold and hence it is not sensitive to the noise power level. Our theoretical and simulation results show that this algorithm works effectively at very low SNR, while being insensitive to time and frequency offsets, and requires no information of the noise's statistics.
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