{"title":"Research on Fast Networking Technologies Based on Hybrid OFDM Modulation for Cognitive Radio Networks","authors":"Zhi-hui Ye, Ziwei Zhang","doi":"10.1109/ICNISC.2017.00020","DOIUrl":null,"url":null,"abstract":"Hybrid OFDM modulation signals are analysis for spectrum correlation in this paper, and are apply to cognitive cooperative networks. Four kinds of channel states of spectrum idle, master signals transmitting, secondary signals transmitting, and hybrid signals transmitting can be distinguished agilely, by using distinct cyclic spectrum features, and embedding exclusive cyclostationary identification artificially, which help to strengthen spectrum characteristic of signal, so as to access and withdraw fast and reliable. Further, by signing different cognitive networks with the locations of hybrid modulation signals, cognitive nodes can identification signals from different networks. Cyclostationary identification and hybrid modulation location are combined to endow the signal the capability of agilely networking. Simulations show that, the proposed model can achieve agilely network building with the improving spectrum efficiency.","PeriodicalId":429511,"journal":{"name":"2017 International Conference on Network and Information Systems for Computers (ICNISC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Network and Information Systems for Computers (ICNISC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNISC.2017.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Hybrid OFDM modulation signals are analysis for spectrum correlation in this paper, and are apply to cognitive cooperative networks. Four kinds of channel states of spectrum idle, master signals transmitting, secondary signals transmitting, and hybrid signals transmitting can be distinguished agilely, by using distinct cyclic spectrum features, and embedding exclusive cyclostationary identification artificially, which help to strengthen spectrum characteristic of signal, so as to access and withdraw fast and reliable. Further, by signing different cognitive networks with the locations of hybrid modulation signals, cognitive nodes can identification signals from different networks. Cyclostationary identification and hybrid modulation location are combined to endow the signal the capability of agilely networking. Simulations show that, the proposed model can achieve agilely network building with the improving spectrum efficiency.