Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to
diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth …

Cognitive radio is an intelligent radio network that has advancement over the traditional
radio. The difference between the traditional and cognitive radio is that all the unused …

In cognitive radio networks, the empty spectrum that is also named as spectrum hole is
detected with the help of spectrum sensing techniques. Energy detection is the most utilized …

Spectrum sensing (SS) is an essential task of the secondary user (SU) in a cognitive radio
system. SS monitors the primary user (PU) activity in order to avoid any collision with SU, as …

In this work, a novel multiband spectrum sensing technique is implemented in the context of
cognitive radios. This technique is based on multiresolution analysis (wavelets), machine …

Cognitive Radio (CR) technology enables secondary users (SUs) to opportunistically access
unused licensed spectrum owned by primary users (PUs). It has the potential to significantly …

Embedding Artificial Intelligence (AI) in integrated circuits is one of the technology pillars of
the so-called digital transformation. Nowadays, the vast majority of electronic devices …

Cogitive radio networks (CRNs) require high capacity and accuracy to detect the presence
of licensed or primary users (PUs) in the sensed spectrum. In addition, they must correctly …

Spectrum sensing is an essential component in cognitive radios (CR). Machine learning
(ML) algorithms are powerful techniques for designing a promising spectrum sensing model …

This paper presents a classification Convolutional Neural Network model for modulation
recognition. The model is capable of classifying 11 different modulation techniques based …