Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …

Blind techniques and algorithms for Multiple-Input Multiple-Output (MIMO) signals
interception have recently attracted a great deal of research efforts. This is due to their …

Modulation recognition is crucial for a good environmental awareness required by cognitive
radio systems. In this study, the authors design and compare models of four among the most …

The prediction of the electric (E) field plays an important role in the monitoring of the
radiofrequency electromagnetic field (RF-EMF) exposure induced by cellular networks. In …

Modulation detection techniques have received much attention in recent years due to their
importance in the military and commercial applications, such as software-defined radio and …

Two-path successive relaying (TPSR) systems have been recently proposed as powerful
candidates for improving the spectral efficiency of cooperative communications. The …

Due to the stochastic nature of wireless channels, the received radio signal is noised during
transmission causing difficulty in classifying radio modulation categories. Deep learning …

Learning from a limited number of samples in automatic modulation classification (AMC) has
garnered considerable attention. However, existing few-shot AMC works solely focus on …

Due to the uncertainty of non-cooperative communication channels, the received signals
often contain various impairment factors, leading to a significant decline in the performance …

Cognitive radio (CR) is the trending domain in addressing the inadequate bands for
communication, and spectrum sensing is the hectic challenge need to be addressed …