Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …

Multiple access (MA) is a crucial part of any wireless system and refers to techniques that
make use of the resource dimensions to serve multiple users/devices/machines/services …

The Internet of Things (IoT) and massive IoT systems are key to sixth-generation (6G)
networks due to dense connectivity, ultrareliability, low latency, and high throughput …

Federated learning (FL) is an emerging paradigm for distributed machine learning that uses
the data and the computational power of user devices while maintaining user privacy (eg …

Recent work has advocated for the use of deep learning to perform power allocation in the
downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are …

Deep neural network-based learning methods have been considered promising techniques
used in beam selection problems. However, existing research ignores the peculiar …

In distributed multiple-input multiple-output (D-MIMO) networks, power control is crucial to
optimize the spectral efficiencies of users and max-min fairness (MMF) power control is a …

The Smart Grid (SG) is an advanced power network that facilitates the two-way exchange of
energy and information between consumers and providers. The field of cyber-physical smart …

Adversarial attacks have the potential to substantially compromise the security of AI-
powered systems and posing high risks especially in the areas like telecommunication …

Machine Learning (ML) is becoming a cornerstone enabling technology for the next
generation of wireless systems. This is mainly due to the high performance achieved by …