Clustering Approach For Distributed Cooperative Detection in Cognitive Radio Networks
Jani Nidhi R1, S.K. Hadia2, Jani Preetida V.3
1Jani Nidhi R., V.T.Patel Department of Electronics & Communication Engineering, C.S. Patel Institute of Technology, Changa (Gujarat), India.
2Prof. S.K. Hadia, V.T.Patel Department of Electronics & Communication Engineering, C.S. Patel Institute of Technology, Changa (Gujarat), India.
3Dr. Jani Preetida V., Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar (Gujarat), India.
Manuscript received on 18 April 2012 | Revised Manuscript received on 25 April 2012 | Manuscript published on 30 April 2012 | PP: 112-116 | Volume-1 Issue-1, April 2012 | Retrieval Number: A0141021112/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There have been significant advancements towards realizations of cognitive radios, as well as towards the development of the various enabling technologies needed for the diverse potential application scenarios of CRs. Nevertheless, we have also seen that a lot of further research and development work is definitely needed before general cognitive wireless networks can be realized. Cognitive radios (CRs) can exploit vacancies in licensed frequency bands to self-organize in opportunistic spectrum networks. Such networks, henceforth referred to as Cognitive Radio Networks (CRNs), operate over a dynamic bandwidth in both time and space. This inherently leads to the partition of the network into clusters depending on the spatial variation of the Primary Radio Network (PRN) activity. Many of the solutions mentioned earlier have been designed only for limited-size CRN, for example due to the presence of centralized controllers. However, we would ideally like to be able to extend such a paradigm to virtually infinite CRNs. In this work, Weighted Clustering Algorithm designed for basic cluster formation for CRNs is proposed, which explicitly can take into account the spatial variations of spectrum opportunities in future.
Keywords: Cognitive Radio, Cooperative sensing, Weighted Clustering Algorithm.
Scope of the Article: Cognitive Radio Networks