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 …

Resource allocation has a direct and profound impact on the performance of vehicle-to-
everything (V2X) networks. In this paper, we develop a hybrid architecture consisting of …

Abstract Internet of Vehicles (IoV) is an evolving and appealing technology which enables
vehicles to communicate with each other, to roadside infrastructures, and to pedestrian …

With the rapid development of Internet of Vehicles (IoV), an increasing number of vehicular
users (VUEs) will connect to the Internet via 5G and beyond 5G (B5G) networks, which …

In recent years, the Internet of Vehicles (IoV) has been found to be of huge potential value in
the promotion of the development of intelligent transportation systems (ITSs) and smart …

In this article, we investigate spectrum allocation in vehicle-to-everything (V2X) network. We
first express the V2X network into a graph, where each vehicle-to-vehicle (V2V) link is a …

Cognitive Internet of Vehicles (CIoV) is an intelligent vehicle network envisioned to
opportunistically access spectrum licensed to primary users (PUs) on the premise of not …

In this paper, we study the joint optimization problem of the spectrum and power allocation
for multiple vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) users in cellular …

Vehicular communications is one of the important applications of 5G communication
systems. The allocation scheme of scarce wireless resources will directly affect the quality of …

Aiming to address the limitations of traditional resource allocation algorithms in the Internet
of Vehicles (IoV), whereby they cannot meet the stringent demands for ultra-low latency and …