Transmission range-aware clustering for green cognitive radio ad hoc networks

The absence of network infrastructure and opportunistic spectrum access in cognitive radio ad hoc networks (CRAHNs) results in connectivity and stability problems. Clustering is known as an effective technique to overcome this problem. Clustering impr...

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Main Authors: Ahmed Osman, Mahassin Mohamed, Syed Yusof, Sharifah Kamilah, Nik Abd. Malik, Nik Noordini, Zubair, Suleiman
格式: Article
出版: University of Electronic Science and Technology of China 2016
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在線閱讀:http://eprints.utm.my/id/eprint/68524/
http://dx.doi.org/10.11989/JEST.1674-862X.603164
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機構: Universiti Teknologi Malaysia
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總結:The absence of network infrastructure and opportunistic spectrum access in cognitive radio ad hoc networks (CRAHNs) results in connectivity and stability problems. Clustering is known as an effective technique to overcome this problem. Clustering improves network performance by implementing a logical network backbone. Therefore, how to efficiently construct this backbone among CRAHNs is of interest. In this paper, we propose a new clustering algorithm for CRAHNs. Moreover, we model a novel cluster head selection function based on the channel heterogeneity in term of transmission ranges. To the best of our knowledge, this is the first attempt to model the channel heterogeneity into the clustering formation in cognitive radio networks. Simulation results show that the performance of clustering is significantly improved by the channel heterogeneity considerations.