This paper focuses primarily on the study of the implementation of Non-orthogonal multiple
access (NOMA) systems on Software defined radio (SDR) platforms, since NOMA has been …

Automatic modulation classification (AMC) using convolutional neural networks (CNNs) is
an active area of research that has the potential to improve the efficiency and reliability of …

Automatic modulation classification (AMC) is an essential technique in intelligent receivers
of non-cooperative communication systems such as cognitive radio networks and military …

Transfer learning (TL) appears to be a potential method for transferring information from
general to specialized activities. Unfortunately, experimenting using various TL models does …

Automatic modulation classification (AMC) of underwater acoustic communication signals is
of great significance in national defense and marine military. Accurate modulation …

Automatic modulation classification (AMC) is an important method for monitoring and
identifying any underwater communication interference. Since the underwater acoustic …

In recent years, Deep Learning (DL) has been successfully applied to detect and classify
Radio Frequency (RF) Signals. A DL approach is especially useful since it identifies the …

Modulation techniques are widely required in communication applications, especially in
wireless communication systems. Thus, it is necessary to classify and recognize types of …

Modulation signal classification in communication systems can be considered a pattern
recognition problem. Earlier works have focused on several feature extraction approaches …

Abstract The fifth-generation (5G) mobile network enhances network connectivity between
many mobile devices by utilizing higher bandwidth with lower communication delay. This …