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Unscented Kalman Filter Based on Spectrum Sensing in a Cognitive Radio Network Using an Adaptive Fuzzy System

1
Department of Information and Communication Engineering, Islamic University, Kushtia 7003, Bangladesh
2
Department of Information and Communication Engineering, Noakhali Science & Technology University, Sonapur 3814, Noakhali, Bangladesh
3
Department of Biomedical Engineering, Islamic University, Kushtia 7003, Banglasesh
4
DiSTA, University of Insubriaz, 21100 Varese, Italy
*
Author to whom correspondence should be addressed.
Current address: Discipline of Information Technology, National University of Ireland Galway, H91 CF50 Galway, Ireland.
These authors contributed equally to this work.
Big Data Cogn. Comput. 2018, 2(4), 39; https://doi.org/10.3390/bdcc2040039
Received: 20 October 2018 / Revised: 13 December 2018 / Accepted: 13 December 2018 / Published: 17 December 2018
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Abstract

In this paper, we proposed the unscented Kalman filter (UKF) based on cooperative spectrum sensing (CSS) scheme in a cognitive radio network (CRN) using an adaptive fuzzy system—in this proposed scheme, firstly, the UKF to apply the nonlinear system which is used to minimize the mean square estimation error; secondly, an adaptive fuzzy logic rule based on an inference engine to estimate the local decisions to detect a licensed primary user (PU) that is applied at the fusion center (FC). After that, the FC makes a global decision by using a defuzzification procedure based on a proposed algorithm. Simulation results show that the proposed scheme achieved better detection gain than the conventional schemes like an equal gain combining (EGC) based soft fusion rule and a Kalman filter (KL) based soft fusion rule under any conditions. Moreover, the proposed scheme achieved the lowest global probability of error compared to both the conventional EGC and KF schemes. View Full-Text
Keywords: cognitive radio network; spectrum sensing; Kalman filter; extended Kalman filter; unscented Kalman filter; fuzzy system cognitive radio network; spectrum sensing; Kalman filter; extended Kalman filter; unscented Kalman filter; fuzzy system
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MDPI and ACS Style

Amin, M.R.; Rahman, M.M.; Hossain, M.A.; Islam, M.K.; Ahmed, K.M.; Singh, B.C.; Miah, M.S. Unscented Kalman Filter Based on Spectrum Sensing in a Cognitive Radio Network Using an Adaptive Fuzzy System. Big Data Cogn. Comput. 2018, 2, 39.

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