Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances

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Spectrum sensing in cognitive radio (2016, background): “A number of test statistics for the problem of spectrum sensing have been proposed in the literature [33, 34, 35].”
End-to-End Learning From Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications (2017, methodology): “Previous research efforts in wireless communication related to signal identification are dominantly based on signal processing tools for communication [5] such as cyclostationary feature detection [6], sometimes in combination with traditional machine learning techniques [7] (e.”
LEO Satellite Constellation for Internet of Things (2017, background): “2) Spectrum Sensing: Spectrum sensing provides the essential information to enable this interweave communications in which primary and secondary users are not allowed to access the medium concurrently [29], including spectral energy, cyclostationary detection and SIR estimation [30], and shares info”
Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications (2017, methodology): “In fact, noise uncertainty has been extensively explored and studied [7][81].”