Cognitive Radio Networks (CRNs) have been proposed as a solution to the problem of
spectrum scarcity in wireless communication systems. CRNs allow for dynamic spectrum …

In electronic warfare systems, detecting low-probability-of-intercept (LPI) radar signals poses
a significant challenge due to the signal power being lower than the noise power …

With the continuous growth of Internet of Things (IoT) deployments, various wireless devices
and communication technologies coexist in industrial environments resulting in a crowded …

In this letter, we propose a novel deep learning-based spectrum sensing scheme using a
multi-antenna receiver. Our main idea is constructing a correlation matrix composed of not …

To address the common issues in traditional convolutional neural network (CNN)-based
spectrum sensing algorithms in cognitive radio networks (CRNs), including inadequate …

Spectrum sensing (SS) is essential in the cognitive radio-enabled Internet of Things (CR-
IoT) to enable spectrum resource allocation. In this study, we propose a novel semantic …

Spectrum sensing is a key technology and prerequisite for Transform Domain
Communication Systems (TDCS). The traditional approach typically involves selecting a …

The limited availability of spectrum resources has been growing into a critical problem in
wireless communications, remote sensing, and electronic surveillance, etc. To address the …

Automatic Modulation Recognition (AMR) plays a crucial role in wireless communication
systems. Deep learning AMR strategies have achieved tremendous success in recent years …

Spectrum sensing based on detection techniques enables cognitive radio networks to detect
vacant frequency bands. The spectrum sensing gives the opportunity to increase the radio …