Abstract
Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.
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CITATION STYLE
Alshawaqfeh, M., Wang, X., Ekti, A. R., Shakir, M. Z., Qaraqe, K., & Serpedin, E. (2015). A survey of machine learning algorithms and their applications in cognitive radio. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 156, pp. 790–801). Springer Verlag. https://doi.org/10.1007/978-3-319-24540-9_66
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