Joint spectrum allocation and power control in vehicular communications based on dueling double DQN

J Ren, Z Chai, Z Chen - Vehicular Communications, 2022 - Elsevier
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 …

Joint Spectrum Allocation and Power Control in Vehicular Networks Based on Reinforcement Learning

K Wang, Y Feng, L Liang, S Jin - … International Symposium on …, 2022 - ieeexplore.ieee.org
In this paper, we investigate the joint channel al-location and power control problem in
vehicular networks. Considering the different quality-of-service (QoS) requirements for …

Meta-reinforcement learning based resource allocation for dynamic V2X communications

Y Yuan, G Zheng, KK Wong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper studies the allocation of shared resources between vehicle-to-infrastructure (V2I)
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …

Multi-Agent Deep Reinforcement Learning for Enhancement of Distributed Resource Allocation in Vehicular Network

O Urmonov, H Aliev, HW Kim - IEEE Systems Journal, 2022 - ieeexplore.ieee.org
To solve a decentralized radio resource management problem in a 5G vehicular network,
we propose a novel resource allocation algorithm based on a multiagent deep …

Deep reinforcement learning based wireless resource allocation for V2X communications

J Li, J Zhao, X Sun - 2021 13th International Conference on …, 2021 - ieeexplore.ieee.org
The shortage and low utilization of air-interface spectrum resources have always been the
bottleneck of the development of vehicle-to-everything (V2X) communications. In this paper …

Deep Reinforcement Learning-Based Resource Allocation for Cellular Vehicular Network Mode 3 with Underlay Approach

J Fu, X Qin, Y Huang, L Tang, Y Liu - Sensors, 2022 - mdpi.com
Vehicle-to-vehicle (V2V) communication has attracted increasing attention since it can
improve road safety and traffic efficiency. In the underlay approach of mode 3, the V2V links …

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning

L Liang, H Ye, GY Li - IEEE Journal on Selected Areas in …, 2019 - ieeexplore.ieee.org
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 based on graph neural networks in vehicular communications

Z He, L Wang, H Ye, GY Li… - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
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 …

[HTML][HTML] Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks

J Zhao, F Hu, J Li, Y Nie - Digital Communications and Networks, 2023 - Elsevier
Abstract In Heterogeneous Vehicle-to-Everything Networks (HVNs), multiple users such as
vehicles and handheld devices and infrastructure can communicate with each other to …

A Deep Reinforcement Learning Scheme for Spectrum Sensing and Resource Allocation in ITS

H Wei, Y Peng, M Yue, J Long, F AL-Hazemi, MM Mirza - Mathematics, 2023 - mdpi.com
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 …