Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …

The key principle of physical layer security (PLS) is to permit the secure transmission of
confidential data using efficient signal-processing techniques. Also, deep learning (DL) has …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Massive multiple-input multiple-output (MIMO) is playing a crucial role in the fifth generation
(5G) and beyond 5G (B5G) communication systems. Unfortunately, the complexity of …

This paper presents channel-aware adversarial attacks against deep learning-based
wireless signal classifiers. There is a transmitter that transmits signals with different …

Although Deep Neural Networks (DNNs) have shown a strong capacity to solve large-scale
problems in many areas, such DNNs with voluminous parameters are hard to be deployed …

We consider a wireless communication system that consists of a transmitter, a receiver, and
an adversary. The transmitter transmits signals with different modulation types, while the …

A comprehensive coverage of the state-of-the-art in quantum machine learning (QML)
methodologies, with a unique perspective on their applications for wireless communications …

Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …

We consider the problem of proactive handoff and beam selection in Terahertz (THz) drone
communication networks assisted with reconfigurable intelligent surfaces (RISs). Drones …