{"title":"Optimal energy harvest-based weighed cooperative spectrum sensing in cognitive radio","authors":"Xin Liu, Junhua Yan, Kunqi Chen","doi":"10.1109/ICCNC.2016.7440554","DOIUrl":null,"url":null,"abstract":"In order to improve sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cognitive radio (CR), an energy harvest-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal, which is then converted into the electric energy to supply the power used for sensing and cooperation. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time and number of cooperative SUs. The simulation results have shown that compared to the traditional cooperative sensing, the proposed cooperative sensing can decrease the energy wastage obviously, and there deed exists an optimal set of sensing time and SU number that maximizes the spectrum access probability.","PeriodicalId":308458,"journal":{"name":"2016 International Conference on Computing, Networking and Communications (ICNC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computing, Networking and Communications (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCNC.2016.7440554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In order to improve sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cognitive radio (CR), an energy harvest-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal, which is then converted into the electric energy to supply the power used for sensing and cooperation. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time and number of cooperative SUs. The simulation results have shown that compared to the traditional cooperative sensing, the proposed cooperative sensing can decrease the energy wastage obviously, and there deed exists an optimal set of sensing time and SU number that maximizes the spectrum access probability.