Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …

A wide variety of works have been conducted in vehicle-to-everything (V2X)
communications to enable a variety of applications for road safety, traffic efficiency and …

The mobile edge computing (MEC) technology can simultaneously provide high-speed
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …

This paper investigates the spectrum sharing problem in vehicular networks based on multi-
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …

In this paper, we develop a novel decentralized resource allocation mechanism for vehicle-
to-vehicle (V2V) communications based on deep reinforcement learning, which can be …

Dynamic topology, fast-changing channels and the time sensitivity of safety-related services
present challenges to the status quo of resource allocation for cellular-underlaying vehicle …

It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …

Vehicular Edge Computing (VEC) is expected to be an effective solution to meet the ultra-
low delay requirements of many emerging Internet of Vehicles (IoV) services by shifting the …

As wireless networks evolve toward high mobility and providing better support for connected
vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular …

The effects of transport development on people's lives are diverse, ranging from economy to
tourism, health care, etc. Great progress has been made in this area, which has led to the …