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Sensors, Networks, Control Systems and Information Processing




Vol. 20, Special Issue, April 2013, pp.27-36



Heterogeneous Network Convergence with Artificial Mapping for Cognitive Radio Networks


1 Hang QIN, 1 Jun SU, 2 Zhengbing HU

1 Computer School, Yangtze University, Jingzhou 434023, China

Tel.: 86-159-7222-1340

2 College of Information Technology, Journalism and Communication,

Huazhong Normal University, Wuhan 430079, China

E-mail: hangqin100@hotmail.com


Received: 5 February 2013  /Accepted: 17 April 2013   /Published: 30 April 2013

Digital Sensors and Sensor Sysstems


Abstract: The artificial mapping scheme is proposed in this paper for adaptive network collaboration of cognitive radio networks. The superiority of the DHT-based overlay for its link state aggregation property, which establishes global convergence for link state aggregation message among a scalable number of nodes, is considered in the analysis. In addition, the fuzzy logic inference can better handle uncertainty, fuzziness, and incomplete information in node convergence report, which is developed as a novel approach to aggregate wireless node control with affordable message overload. The Artificial Mapping Tree (AMT) for the new convergence scheme is verified by the simulation and experimental results. The moderately increased network throughput for convergence validation is demonstrated with the proactive spectrum coordination.


Keywords: Leave cognitive radio networks, Heterogeneous architecture, Artificial mapping, Fuzzy logic inferences, Dynamic resource management


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