Multiagent deep-reinforcement-learning-based resource allocation for heterogeneous QoS guarantees for vehicular networks
Vehicle-to-vehicle communications can offer direct information interaction, including security-
centered information and entertainment information. However, the rapid proliferation of …
centered information and entertainment information. However, the rapid proliferation of …
Federated multi-agent deep reinforcement learning for resource allocation of vehicle-to-vehicle communications
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 …
present challenges to the status quo of resource allocation for cellular-underlaying vehicle …
Meta-reinforcement learning based resource allocation for dynamic V2X communications
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 …
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …
Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
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 …
DDPG-based resource management for MEC/UAV-assisted vehicular networks
In this paper, we investigate joint vehicle association and multi-dimensional resource
management in a vehicular network assisted by multi-access edge computing (MEC) and …
management in a vehicular network assisted by multi-access edge computing (MEC) and …
Deep reinforcement learning for multi-objective resource allocation in multi-platoon cooperative vehicular networks
Y Xu, K Zhu, H Xu, J Ji - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Grouping vehicles into platoons is a promising cooperative driving scenario to enhance the
traffic safety and capacity of future vehicular networks. However, fast changing channel …
traffic safety and capacity of future vehicular networks. However, fast changing channel …
Deep-reinforcement-learning-based mode selection and resource allocation for cellular V2X communications
Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
[HTML][HTML] DRL-based intelligent resource allocation for diverse QoS in 5G and toward 6G vehicular networks: a comprehensive survey
The vehicular network is taking great attention from both academia and industry to enable
the intelligent transportation system (ITS), autonomous driving, and smart cities. The system …
the intelligent transportation system (ITS), autonomous driving, and smart cities. The system …
Aoi-aware joint spectrum and power allocation for internet of vehicles: A trust region policy optimization-based approach
In Internet of Vehicles (IoV), information freshness is a significant indicator to indemnify road
traffic safety, which is measured by Age of Information (AoI). In this article, we consider the …
traffic safety, which is measured by Age of Information (AoI). In this article, we consider the …
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