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A Distributed Message-passing Approach for Clustering Cognitive Radio Networks

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Abstract

Forming collaborative wireless network clusters in dynamically changing environments is essential for cognitive radios to achieve such desired objectives as interference resilience and low communications overhead. In this paper, a novel approach to form efficient node clusters in an ad hoc cognitive radio network (CRN) is introduced based on the affinity propagation (AP) message-passing technique. With this approach, nodes exchange messages containing local network information with their direct neighbours until a high quality set of clusterheads and an efficient cluster structure emerges. The groupings are based on measures of similarity between the network nodes, which are selected based on application requirements. As an initial application, we show how the AP technique can be used to distributively determine cluster assignments and elect a small number of clusterheads that cover a CRN. Such an objective is commonly used to reduce communication overhead in key network functions such as resource management and routing table maintenance. To demonstrate the merits of the proposed approach, the clustering efficiency of the AP technique is evaluated on randomly generated open spectrum access scenarios. The simulation results demonstrate that the proposed approach provides a smaller number of clusters than a standard technique based on approximating the minimum dominating sets of the corresponding ad hoc network graphs.

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Correspondence to Kareem E. Baddour.

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Parts of this paper have been presented at the 2nd Workshop on Cognitive Networks and Communications (COGCOM 2009).

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Baddour, K.E., Üreten, O. & Willink, T.J. A Distributed Message-passing Approach for Clustering Cognitive Radio Networks. Wireless Pers Commun 57, 119–133 (2011). https://doi.org/10.1007/s11277-010-0010-z

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