… This study presents a new machine learning (support vector machine (SVM))-based cooperative
spectrum sensing (CSS) model, which utilises the methods of user grouping, to reduce …

… In this work, three specific machine learning techniques (neural networks, expectation
maximization and k-means) are applied to a multiband spectrum sensing technique for cognitive …

… based on Bayesian machine learning. We exploit the mobility of multiple SUs to simultaneously
collect spectrum sensing data and cooperatively derive the global spectrum states. We …

… sensing duration and assure the sensing accuracy, which means the good sensing accuracy
is obtained when the sensing … the sensing accuracy with short spectrum sensing duration. …

… an efficient spectrum sensing technique for cooperative wideband spectrum access that
overcomes the shortcomings of conventional approaches. It combines machine learning with …

… spectrum sensing framework for MPTP scenario based on machine learning techniques. …
In this paper, we proposed a new machine learning based sensing framework, which combined …

… Spectrum sensing is a fundamental task of CR and is … Popular spectrum sensing methods
include the energy detection [… a new spectrum sensing approach based on machine learning …

… Spectrum sensing is one of the most important processes performed by CR systems. In our
work, we consider an SU spectrum sensor with 1 antenna (represented by the RTL-SDR in …

… As seen in Figure 6, we compared the proposed hybrid ML-based spectrum sensing method
with the base spectrum sensing techniques such as energy detection and matched filter …

… In the context of spectrum sensing, machine learning approaches have also been proposed
in the literature [9, 10]. In particular, [10] proposed a DL based spectrum sensing method for …