Motivated by the superior performance of deep learning in many applications including
computer vision and natural language processing, several recent studies have focused on …

Deep learning algorithms have been shown to be powerful in many communication network
design problems, including that in automatic modulation classification. However, they are …

Deep learning (DL) is a powerful technique for many real-time applications, but it is
vulnerable to adversarial attacks. Herein, we consider DL-based modulation classification …

Deep learning is increasingly being used for many tasks in wireless communications, such
as modulation classification. However, it has been shown to be vulnerable to adversarial …

Although Deep Neural Networks (DNN) can achieve state-of-the-art performance in
automatic modulation recognition (AMC) tasks, they have sufferd tremendous failures from …

Deep learning-based automatic modulation classification (AMC) models are susceptible to
adversarial attacks. Such attacks inject specifically crafted wireless interference into …

Automatic modulation classification (AMC) is used in intelligent receivers operating in
shared spectrum environments to classify the modulation constellation of radio frequency …

Automatic modulation classification (AMC) technology plays a vital role in the sixth
generation mobile system (6G). However, deep learning (DL) based AMC models possess …

Deep Learning has attracted significant interests in wireless communication design
problems. However, recent studies discovered that the deep neural network is vulnerable to …

Deep neural network (DNN) greatly improves the efficiency of modulation recognition in
wireless communication, but it also suffers from attacks. Generative artificial intelligence …