Multi-Cell Cooperative Resource Allocation and Performance Evaluation for Roadside-Assisted Automated Driving

S Yang, X Zhu, Y Li, Q Yuan, L Li - World Electric Vehicle Journal, 2024 - mdpi.com
The proliferation of wireless technologies, particularly the advent of 5G networks, has
ushered in transformative possibilities for enhancing vehicular communication systems …

Federated multi-agent deep reinforcement learning for resource allocation of vehicle-to-vehicle communications

X Li, L Lu, W Ni, A Jamalipour… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

Vehicular network spectrum allocation using hybrid NOMA and multi-agent reinforcement learning

LE Alatabani, RA Saeed, ES Ali, RA Mokhtar… - … and Delivering Practical …, 2023 - Springer
The recent years have seen a proven impact of the reinforcement learning use in many
applications which showed tremendous success in solving many decision-making …

Multi-Agent Reinforcement Learning Aided Resources Allocation Method in Vehicular Networks

Y Ji, X Zhang, Y Wang, H Gacanin… - 2022 IEEE 96th …, 2022 - ieeexplore.ieee.org
To address the problem of spectrum resources and transmitting power for vehicular
networks, this paper proposes a resource allocation (RA) method based on dueling double …

DRL-based RAT Selection in a Hybrid Vehicular Communication Network

BY Yacheur, T Ahmed… - 2023 IEEE 97th Vehicular …, 2023 - ieeexplore.ieee.org
Cooperative intelligent transport systems rely on a set of Vehicle-to-Everything (V2X)
applications to enhance road safety. Emerging new V2X applications like Advanced Driver …

TacNet: A Tactic-Interactive Resource Allocation Method for Vehicular Networks

X Fu, Q Yuan, Z Zhuang, Y Li, J Liao… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
To support safety driving and various on-board services, efficient resource allocation is
crucial for the promising implement of vehicle platooning in intelligent transportation systems …

Multi-agent deep reinforcement learning-empowered channel allocation in vehicular networks

AS Kumar, L Zhao, X Fernando - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Channel allocation has a direct and profound impact on the performance of vehicle-to-
everything (V2X) networks. Considering the dynamic nature of vehicular environments, it is …

Multi-agent RL enables decentralized spectrum access in vehicular networks

P Xiang, H Shan, M Wang, Z Xiang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we investigate the joint sub-channel and power allocation problem for cellular
vehicle-to-everything (V2X) communications, where multiple vehicle-to-infrastructure (V2I) …

Communication-efficient multi-agent actor-critic framework for distributed optimization of resource allocation in V2X networks

N Hammami, KK Nguyen - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
The vehicular communication technology has enabled new services for drivers and
passengers with different Quality of Service (QoS) demands. Due to network resource …

A Hybrid Multi-Agent Reinforcement Learning Approach for Spectrum Sharing in Vehicular Networks

M Jamal, Z Ullah, M Naeem, M Abbas, A Coronato - Future Internet, 2024 - mdpi.com
Efficient spectrum sharing is essential for maximizing data communication performance in
Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that …