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

Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …

Special attention has been devoted to joint wireless communication and radar sensing
concepts over the past decades. Considerable confusion arose, however, with regard to …

The sixth generation (6G) of mobile communication system is witnessing a new paradigm
shift, ie, integrated sensing-communication system. A comprehensive dataset is a …

With the development of the technologies for Vehicle-to-Everything (V2X), driving
information sharing leads to a potential solution for intelligent vehicles to enhance their …

A fundamental issue of the vehicular digital twin (DT) is efficiently synchronizing the data
between the DT and the vehicular user (VUE). In this paper, we consider the heterogeneous …

Deep learning (DL) is an emerging paradigm for accurate channel estimation for intelligent
reflecting surface (IRS)-aided wireless communication systems. It has been proven to be a …

The advanced Internet of Things (IoT) technique has provided a promising vision in
emergency response issues with its convenience in environment cognition and …

In this letter, we introduce integrated sensing and communications (ISAC) to multi-hop
vehicle-to-vehicle (V2V) networks and aim to augment end-to-end information delivery. As …

Edge-device co-inference refers to deploying well-trained artificial intelligent (AI) models at
the network edge under the cooperation of devices and edge servers for providing ambient …