Resource allocation based on graph neural networks in vehicular communications
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 …
first express the V2X network into a graph, where each vehicle-to-vehicle (V2V) link is a …
Learn to compress CSI and allocate resources in vehicular networks
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 …
everything (V2X) networks. In this paper, we develop a hybrid architecture consisting of …
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 …
systems. The allocation scheme of scarce wireless resources will directly affect the quality of …
Spectrum sharing in vehicular networks based on multi-agent reinforcement learning
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 …
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …
A deep learning based resource allocation scheme in vehicular communication systems
In vehicular communications, intracell interference and the stringent latency requirement are
challenging issues. In this paper, a joint spectrum reuse and power allocation problem is …
challenging issues. In this paper, a joint spectrum reuse and power allocation problem is …
Resource allocation in vehicular communications using graph and deep reinforcement learning
Cellular based vehicle-to-everything (V2X) communications have recently gained more
interest from both academia and industry. However, there exist many challenges in cellular …
interest from both academia and industry. However, there exist many challenges in cellular …
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 …
everything (V2X) networks. Considering the dynamic nature of vehicular environments, it is …
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 …
improve road safety and traffic efficiency. In the underlay approach of mode 3, the V2V links …
Deep reinforcement learning-based spectrum allocation algorithm in Internet of vehicles discriminating services
Z Guan, Y Wang, M He - Applied Sciences, 2022 - mdpi.com
With the rapid development of global automotive industry intelligence and networking, the
Internet of Vehicles (IoV) service, as a key communication technology, has been faced with …
Internet of Vehicles (IoV) service, as a key communication technology, has been faced with …
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 …
bottleneck of the development of vehicle-to-everything (V2X) communications. In this paper …