{"title":"crn中的盲频谱感知算法综述","authors":"Doaa J. Zaidawi, S. Sadkhan","doi":"10.1109/IEC52205.2021.9476142","DOIUrl":null,"url":null,"abstract":"In cognitive radio, the spectrum is being used in those modern applications that can monitor spectrum, i.e., alternative users (SUs), could use the spectrum that the main user (PU) does not actually control. Any stakeholders have found out that the approved spectrum is not in operation all the time/locations. To maximize spectrum usage, SUs are enabled to get access to frequency bands already allocated to PUs while they are not using it, under the condition that the SUs do not interact with the PU. To avoid interference to the PU, the SU CR faces a difficult task, i.e., detecting the existence of the PU signal in low-SNR (negative dB) area. This is due to signal attenuation due to multipath and shadowing that can occur before the signal hits the SU. For sensing, the energy detectors are commonly used, but they suffer from the noise uncertainty issue in such noise conditions. The SNR wall is the operating threshold at which image identification is no longer possible. This ambiguity is due to how imprecise the calculations of noise variance are over time, and due to the changing noise variance. In this article, a short overview is given for researchers in the field of cognitive radio technology (CRNs).","PeriodicalId":374702,"journal":{"name":"2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic\" (IEC)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Blind Spectrum Sensing Algorithms in CRNs: A Brief Overview\",\"authors\":\"Doaa J. Zaidawi, S. Sadkhan\",\"doi\":\"10.1109/IEC52205.2021.9476142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In cognitive radio, the spectrum is being used in those modern applications that can monitor spectrum, i.e., alternative users (SUs), could use the spectrum that the main user (PU) does not actually control. Any stakeholders have found out that the approved spectrum is not in operation all the time/locations. To maximize spectrum usage, SUs are enabled to get access to frequency bands already allocated to PUs while they are not using it, under the condition that the SUs do not interact with the PU. To avoid interference to the PU, the SU CR faces a difficult task, i.e., detecting the existence of the PU signal in low-SNR (negative dB) area. This is due to signal attenuation due to multipath and shadowing that can occur before the signal hits the SU. For sensing, the energy detectors are commonly used, but they suffer from the noise uncertainty issue in such noise conditions. The SNR wall is the operating threshold at which image identification is no longer possible. This ambiguity is due to how imprecise the calculations of noise variance are over time, and due to the changing noise variance. In this article, a short overview is given for researchers in the field of cognitive radio technology (CRNs).\",\"PeriodicalId\":374702,\"journal\":{\"name\":\"2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic\\\" (IEC)\",\"volume\":\"105 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic\\\" (IEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEC52205.2021.9476142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic\" (IEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEC52205.2021.9476142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind Spectrum Sensing Algorithms in CRNs: A Brief Overview
In cognitive radio, the spectrum is being used in those modern applications that can monitor spectrum, i.e., alternative users (SUs), could use the spectrum that the main user (PU) does not actually control. Any stakeholders have found out that the approved spectrum is not in operation all the time/locations. To maximize spectrum usage, SUs are enabled to get access to frequency bands already allocated to PUs while they are not using it, under the condition that the SUs do not interact with the PU. To avoid interference to the PU, the SU CR faces a difficult task, i.e., detecting the existence of the PU signal in low-SNR (negative dB) area. This is due to signal attenuation due to multipath and shadowing that can occur before the signal hits the SU. For sensing, the energy detectors are commonly used, but they suffer from the noise uncertainty issue in such noise conditions. The SNR wall is the operating threshold at which image identification is no longer possible. This ambiguity is due to how imprecise the calculations of noise variance are over time, and due to the changing noise variance. In this article, a short overview is given for researchers in the field of cognitive radio technology (CRNs).