The article analyzes the problem of energy efficient techniques in cooperative spectrum
sensing (CSS). Although it was proven that single-device sensing is not sufficient for reliable …

We study cooperative spectrum sensing in cognitive radio networks (CRN) using machine
learning techniques in this paper. A low-dimensional probability vector is proposed as the …

Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio
network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects …

We propose a novel cluster based cooperative spectrum sensing algorithm to save the
wastage of energy, in which clusters are formed using fuzzy c-means (FCM) clustering and a …

Ultra-densification is one of the main features of 5G networks. In an ultra-dense network,
how to conduct interference management and spectrum allocation is a challenging issue …

In cognitive radio networks (CRNs), localization of primary users (PUs) and secondary users
(SUs) can enable several key capabilities such as location aware routing and power control …

Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

This work explores the scope of Fuzzy C-Means (FCM) clustering on energy detection based
cooperative spectrum sensing (CSS) in single primary user (PU) cognitive radio network …

Machine learning based approaches for spectrum sensing and spectrum occupancy
prediction in cognitive radio applications appear to have attracted sufficient interest in the …

Cooperative spectrum sensing (CSS) is an effective approach to improve the detection
performance in cognitive radio (CR) networks. The CSS process imposes some additional …