We are on the cusp of a new era of connected autonomous vehicles with unprecedented
user experiences, tremendously improved road safety and air quality, highly diverse …

Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …

Sixth generation (6G) internet of things (IoT) networks will modernize the applications and
satisfy user demands through implementing smart and automated systems. Intelligence …

Future wireless communication is expected to be a paradigm shift from three basic service
requirements of 5th Generation (5G) including enhanced Mobile Broadband (eMBB), Ultra …

This paper considers machine learning for physical layer security design for communication
in a challenging wireless environment. The radio environment is assumed to be …

At cellular wireless communication systems, channel estimation (CE) is one of the key
techniques that are used in Orthogonal Frequency Division Multiplexing modulation …

In vehicular networks, radio-frequency (RF) jamming attacks are considered a major threat
to the availability of control channel (CCH). In particular, vehicles may not be able to receive …

This paper investigates a machine learning-based power allocation design for secure
transmission in a cognitive radio (CR) network. In particular, a neural network (NN)-based …

Beam tracking is a core issue in 5G vehicle-to-everything (V2X) networks. Specifically,
higher beamforming gain is required to compensate for the path loss at higher frequencies …