Abstract
An energy detection based cooperative spectrum sensing approach using Fuzzy c-means clustering is proposed in this work for cognitive radio system. The objective here is to categorize first the measured PU energy contents into multiple classes to highlight the relative degree in presence or absence of PU and Fuzzy c-means (FCM) algorithm is utilized for this purpose. A soft decision based spectrum sensing is proposed here to categorize the presence or absence of PU in four different classes which then develop individual binary decision functions. Resultant binary decision function is then developed using OR fusion rule. Simulation results highlight that the proposed scheme provides high detection probability at low diversity and less number of samples. The results are further compared with the performance of the conventional energy detector methods to highlight the significance of the proposed scheme.
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Chatterjee, S., Banerjee, A., Acharya, T., Maity, S.P. (2014). Fuzzy C-Means Clustering in Energy Detection for Cooperative Spectrum Sensing in Cognitive Radio System. In: Jonsson, M., Vinel, A., Bellalta, B., Belyaev, E. (eds) Multiple Access Communications. MACOM 2014. Lecture Notes in Computer Science, vol 8715. Springer, Cham. https://doi.org/10.1007/978-3-319-10262-7_8
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DOI: https://doi.org/10.1007/978-3-319-10262-7_8
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