{"title":"Energy detection based cooperative spectrum sensing using fuzzy conditional entropy maximization","authors":"A. Banerjee, S. Maity","doi":"10.1109/ANTS.2014.7057228","DOIUrl":null,"url":null,"abstract":"An Energy detection based cooperative spectrum sensing for cognitive radio system is proposed in this paper using fuzzy conditional entropy maximization. Instead of using conventional single threshold in energy value, this paper deals with utilization of multiple thresholds to improve the sensing reliability. The basic objective here is to calculate an optimal set of fuzzy parameters that would maximize the fuzzy conditional entropy and Differential Evolution algorithm is used for this purpose. Multiple threshold values are calculated using these optimal parameters. Simulation results highlight improved performance of the proposed scheme by providing high detection probability at low diversity and using less number of samples. Performance results are compared with the conventional cooperative energy detector methods to highlight the significance of the proposed scheme.","PeriodicalId":333503,"journal":{"name":"2014 IEEE International Conference on Advanced Networks and Telecommuncations Systems (ANTS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Advanced Networks and Telecommuncations Systems (ANTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTS.2014.7057228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
An Energy detection based cooperative spectrum sensing for cognitive radio system is proposed in this paper using fuzzy conditional entropy maximization. Instead of using conventional single threshold in energy value, this paper deals with utilization of multiple thresholds to improve the sensing reliability. The basic objective here is to calculate an optimal set of fuzzy parameters that would maximize the fuzzy conditional entropy and Differential Evolution algorithm is used for this purpose. Multiple threshold values are calculated using these optimal parameters. Simulation results highlight improved performance of the proposed scheme by providing high detection probability at low diversity and using less number of samples. Performance results are compared with the conventional cooperative energy detector methods to highlight the significance of the proposed scheme.