Hierarchical Cognition Cycle for Cognitive Radio Networks

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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. Cognitive radio (CR) can bring about remarkable improvement in spectrum utilization. Differentiated 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 indis indispensable aspects and the connection between they.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. Still more, a few research challenges ahead are presented a s well.
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