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http://dx.doi.org/10.7840/kics.2014.39B.11.790

Efficient Spectrum Sensing Based on Evolutionary Game Theory in Cognitive Radio Networks  

Kang, Keon-Kyu (Multimedia Network Laboratory Inha University)
Yoo, Sang-Jo (Multimedia Network Laboratory Inha University)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.39B, no.11, 2014 , pp. 790-802 More about this Journal
Abstract
In cognitive radio technology, secondary users can determine the absence of PU by periodic sensing operation and cooperative sensing between SUs yields a significant sensing performance improvement. However, there exists a trade off between the gains in terms of probability of detection of the primary users and the costs of false alarm probability. Therefore, the cooperation group must maintain the suitable size. And secondary users should sense not only the currently using channels and but also other candidates channel to switch in accordance with sudden appearance of the primary user. In this paper, we propose an effective group cooperative sensing algorithm in distributed network situations that is considering both of inband and outband sensing using evolutionary game theory. We derived that the strategy group of secondary users converges to an ESS(Evolutionary sable state). Using a learning algorithm, each secondary user can converge to the ESS without the exchange of information to each other.
Keywords
cognitive radio; evolutionary game; cooperative sensing; outband sensing; payoff function;
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