Cognitive radio(CR) can bring about remarkable improvement in spectrum utilization.Different cognition cycles have been proposed in recent years.However,most of the existing works only emphasize functional or operatio...Cognitive radio(CR) can bring about remarkable improvement in spectrum utilization.Different cognition cycles have been proposed in recent years.However,most of the existing works only emphasize functional or operational aspects of cognition cycle,regardless of other indispensable aspects and the connection between them.To deal with the emerging situation of "data rich,information vague,knowledge poor" in cognitive radio networks(CRNs),we propose the hierarchical cognition cycle(HCC) as a new transdisciplinary research field in this paper.HCC investigates a fundamental problem,which is how to manage available resources in the complex environment to meet various demands in CRN.A comprehensive theoretical framework of HCC is established in terms of the core,the essence loop,the function loop,the operation loop,and the external loop of HCC.The reduction of uncertainty in CRN is studied and several new metrics in HCC are defined.Furthermore,a few research challenges ahead are presented as well.展开更多
This paper considers partial function linear models of the form Y =∫X(t)β(t)dt + g(T)with Y measured with error. The authors propose an estimation procedure when the basis functions are data driven, such as with fun...This paper considers partial function linear models of the form Y =∫X(t)β(t)dt + g(T)with Y measured with error. The authors propose an estimation procedure when the basis functions are data driven, such as with functional principal components. Estimators of β(t) and g(t) with the primary data and validation data are presented and some asymptotic results are given. Finite sample properties are investigated through some simulation study and a real data application.展开更多
基金supported by the National Key Basic Research Program of China(973 Program) under Grant No.2009CB320400the National Natural Science Foundation of China under Grants No.60932002,61172062,61301160the Natural Science Foundation of Jiangsu,China under Grant No.BK2011116
文摘Cognitive radio(CR) can bring about remarkable improvement in spectrum utilization.Different cognition cycles have been proposed in recent years.However,most of the existing works only emphasize functional or operational aspects of cognition cycle,regardless of other indispensable aspects and the connection between them.To deal with the emerging situation of "data rich,information vague,knowledge poor" in cognitive radio networks(CRNs),we propose the hierarchical cognition cycle(HCC) as a new transdisciplinary research field in this paper.HCC investigates a fundamental problem,which is how to manage available resources in the complex environment to meet various demands in CRN.A comprehensive theoretical framework of HCC is established in terms of the core,the essence loop,the function loop,the operation loop,and the external loop of HCC.The reduction of uncertainty in CRN is studied and several new metrics in HCC are defined.Furthermore,a few research challenges ahead are presented as well.
基金supported by the National Natural Science Foundation of China under Grant Nos.11561006 and 11471127Master Foundation of Guangxi University of Technology under Grant No.070235+2 种基金Doctoral Foundation of Guangxi University of Science and Technology under Grant No.14Z07Research Projects of Colleges and Universities in Guangxi under Grant No.KY2015YB171the Open Fund Project of Guangxi Colleges and Universities Key Laboratory of Mathematics and Statistical Model under Grant No.2016GXKLMS005
文摘This paper considers partial function linear models of the form Y =∫X(t)β(t)dt + g(T)with Y measured with error. The authors propose an estimation procedure when the basis functions are data driven, such as with functional principal components. Estimators of β(t) and g(t) with the primary data and validation data are presented and some asymptotic results are given. Finite sample properties are investigated through some simulation study and a real data application.
