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An Efficient Cooperative Neighbor Discovery Framework of Cognitive Radio Ad-Hoc Networks for Future Internet of Things

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Abstract

In the paper, an efficient cooperative neighbor discovery framework for cognitive radio ad-hoc networks (CRAHNs) is proposed for future internet of things. Unlike classical ad-hoc networks, users in a CRAHN do not have a pre-allocated set of channels or common control channel (CCC), which makes the situation much more complicated in neighbor discovery. The proposed framework addresses these issues in the absence of a central controller and a CCC, and can discover a large number of neighbors within a limited time. The absence of a CCC necessitates channel hopping to search for new neighbors, which can be time-consuming with a large number of available channels. In the proposed scheme, a node expedites the rate of neighbor discovery by choosing only a subset of available channels for hopping and working in a group. In addition, while working in a group, the nodes are assigned disjoint sets of channels so that different nodes explore different channels at the same time to discover new neighbors. Simulation results show that the proposed scheme outperforms the random channel hopping scheme which takes whole available channel set to search for neighbors.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2063779).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, International Islamic University Chittagong, Kumira, Sitakunda, Chittagong, Bangladesh

    Adil Mahmud

  2. School of Electrical Electronic Engineering, University of Ulsan, Mugeo-Dong, Nam-Gu, Ulsan, 680-749, Korea

    Young-Doo Lee & In-Soo Koo

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  1. Adil Mahmud
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  2. Young-Doo Lee
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  3. In-Soo Koo
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Correspondence to In-Soo Koo.

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Mahmud, A., Lee, YD. & Koo, IS. An Efficient Cooperative Neighbor Discovery Framework of Cognitive Radio Ad-Hoc Networks for Future Internet of Things. Wireless Pers Commun 91, 1603–1620 (2016). https://doi.org/10.1007/s11277-015-3143-2

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