Enhancing Vehicular Networks With Hierarchical O-RAN Slicing and Federated DRL
With 5G technology evolving, Open Radio Access Network (O-RAN) solutions are becoming
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular …
Deep reinforcement learning-based RAN slicing for UL/DL decoupled cellular V2X
The emerging uplink (UL) and downlink (DL) decoupled radio access networks (RAN) has
attracted a lot of attention due to the significant gains in network throughput, load balancing …
attracted a lot of attention due to the significant gains in network throughput, load balancing …
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 …
Semi-decentralized network slicing for reliable V2V service provisioning: A model-free deep reinforcement learning approach
Applying of network slicing in vehicular networks becomes a promising paradigm to support
emerging Vehicle-to-Vehicle (V2V) applications with diverse quality of service (QoS) …
emerging Vehicle-to-Vehicle (V2V) applications with diverse quality of service (QoS) …
A Multi-Level Deep RL-Based Network Slicing and Resource Management for O-RAN-Based 6G Cell-Free Networks
N Ghafouri, JS Vardakas, K Ramantas… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the deployment of the fifth generation (5G) of cellular networks, the focus of the
information society has switched to the next era in which the limitations of 5G will be …
information society has switched to the next era in which the limitations of 5G will be …
Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …
services is being widely studied and a hot topic for the latest research works in the literature …
Performance vs. Cost Tradeoff for Network Slicing in Open RAN: An Intelligent Hierarchical Algorithm for Flexible Utility-Control
The emergence of sophisticated applications and vertical services results in ever more
complex mobile networks. Hence radio access network (RAN) slicing based on the …
complex mobile networks. Hence radio access network (RAN) slicing based on the …
5G vehicular network resource management for improving radio access through machine learning
The current cellular technology and vehicular networks cannot satisfy the mighty strides of
vehicular network demands. Resource management has become a complex and …
vehicular network demands. Resource management has become a complex and …
Multi-agent reinforcement learning for slicing resource allocation in vehicular networks
Y Cui, H Shi, R Wang, P He, D Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To support diverse Internet of vehicles (IoV) services with different quality of service (QoS)
requirements, network slicing is applied in vehicular networks to establish multiple logically …
requirements, network slicing is applied in vehicular networks to establish multiple logically …
[引用][C] A Deep Reinforcement Learning based 5G-RAN Slicing Strategy for V2X Services
Vehicular communication is a key technology in intelligent transportation systems which
links vehicles, roadside units, and pedestrians. One of the key factor for providing design …
links vehicles, roadside units, and pedestrians. One of the key factor for providing design …