Machine Learning Techniques for Cooperative Spectrum Sensing in Cognitive Radio Networks

@article{Thilina2013MachineLT,
  title={Machine Learning Techniques for Cooperative Spectrum Sensing in Cognitive Radio Networks},
  author={Karaputugala Madushan Thilina and Kae Won Choi and Nazmus Saquib and Ekram Hossain},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2013},
  volume={31},
  pages={2209-2221}
}
We propose novel cooperative spectrum sensing (CSS) algorithms for cognitive radio (CR) networks based on machine learning techniques which are used for pattern classification. In this regard, unsupervised (e.g., K-means clustering and Gaussian mixture model (GMM)) and supervised (e.g., support vector machine (SVM) and weighted K-nearest-neighbor (KNN)) learning-based classification techniques are implemented for CSS. For a radio channel, the vector of the energy levels estimated at CR devices… CONTINUE READING
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