Cooperative Cognitive Radio Networks: The Complete Spectrum Cycle provides a solid
understanding of the foundations of cognitive radio technology, from spectrum sensing …

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

We consider novel cooperative spectrum sensing (CSS) algorithms based on the pattern
classification techniques for cognitive radio (CR) networks. In this regard, support vector …

In this article, a technique for cooperative spectrum sensing (CSS) using the Extreme
Learning Machine (ELM) is proposed. ELMs are feedforward neural networks where the …

Spectrum sensing remains a challenge in the context of cognitive radio networks (CRNs).
Compared with traditional single-user sensing, cooperative spectrum sensing (CSS) exploits …

Given an image region of pixels, second order statistics can be used to construct a
descriptor for object representation. One example is the covariance matrix descriptor, which …

Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-
generation (5G). Nevertheless, it is relatively complex when applying NOMA to a massive …

Green cognitive radios show promise for high energy efficiency (EE) in the future of wireless
communications. Spectrum sensing refers to an energy-consuming procedure that allows …

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

Spectrum sensing is the most crucial importance in cognitive radios. We propose a novel
machine-learning algorithm for spectrum sensing in cognitive radio networks, which plays …