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http://dx.doi.org/10.3837/tiis.2012.01.016

Cooperative Spectrum Sensing using Kalman Filter based Adaptive Fuzzy System for Cognitive Radio Networks  

Thuc, Kieu-Xuan (School of Electrical Engineering, University of Ulsan)
Koo, In-Soo (School of Electrical Engineering, University of Ulsan)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.6, no.1, 2012 , pp. 287-304 More about this Journal
Abstract
Spectrum sensing is an important functionality for cognitive users to look for spectrum holes before taking transmission in dynamic spectrum access model. Unlike previous works that assume perfect knowledge of the SNR of the signal received from the primary user, in this paper we consider a realistic case where the SNR of the primary user's signal is unknown to both fusion center and cognitive radio terminals. A Kalman filter based adaptive Takagi and Sugeno's fuzzy system is designed to make the global spectrum sensing decision based on the observed energies from cognitive users. With the capacity of adapting system parameters, the fusion center can make a global sensing decision reliably without any requirement of channel state information, prior knowledge and prior probabilities of the primary user's signal. Numerical results prove that the sensing performance of the proposed scheme outperforms the performance of the equal gain combination based scheme, and matches the performance of the optimal soft combination scheme.
Keywords
CR; cooperative spectrum sensing; Kalman filter; adaptive fuzzy system; data fusion;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)  (Related Records In Web of Science)
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