A novel duplex deep reinforcement learning based RRM framework for next-generation V2X communication networks
Resource management in the next-generation vehicle-to-everything (V2X) communication
networks is a demanding research problem. It is difficult to achieve the best results if the …
networks is a demanding research problem. It is difficult to achieve the best results if the …
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 …
[HTML][HTML] Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks
Abstract In Heterogeneous Vehicle-to-Everything Networks (HVNs), multiple users such as
vehicles and handheld devices and infrastructure can communicate with each other to …
vehicles and handheld devices and infrastructure can communicate with each other to …
Spectrum-Energy-Efficient Mode Selection and Resource Allocation for Heterogeneous V2X Networks: A Federated Multi-Agent Deep Reinforcement Learning …
Heterogeneous communication environments and broadcast feature of safety-critical
messages bring great challenges to mode selection and resource allocation problem. In this …
messages bring great challenges to mode selection and resource allocation problem. In this …
QoS based deep reinforcement learning for V2X resource allocation
S Bhadauria, Z Shabbir… - … Black Sea conference …, 2020 - ieeexplore.ieee.org
The 3rd generation partnership project (3GPP) standard has introduced vehicle to
everything (V2X) communi-cation in Long Term Evolution (LTE) to pave the way for future …
everything (V2X) communi-cation in Long Term Evolution (LTE) to pave the way for future …
Toward enhanced reinforcement learning-based resource management via digital twin: Opportunities, applications, and challenges
This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework
aimed at optimizing performance and reliability in network resource management, since the …
aimed at optimizing performance and reliability in network resource management, since the …
A joint power and bandwidth allocation method based on deep reinforcement learning for V2V communications in 5G
X Hu, S Xu, L Wang, Y Wang, Z Liu, L Xu… - China …, 2021 - ieeexplore.ieee.org
Vehicular communications have recently attracted great interest due to their potential to
improve the intelligence of the transportation system. When maintaining the high reliability …
improve the intelligence of the transportation system. When maintaining the high reliability …
FAQ: A fuzzy-logic-assisted Q learning model for resource allocation in 6G V2X
This research proposes a dynamic resource allocation method for vehicle-to-everything
(V2X) communications in the sixth generation (6G) cellular networks. Cellular V2X (C-V2X) …
(V2X) communications in the sixth generation (6G) cellular networks. Cellular V2X (C-V2X) …
Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications
YC Chung, HY Chang, RY Chang… - 2023 IEEE 97th …, 2023 - ieeexplore.ieee.org
Vehicle-to-everything (V2X) communication is an essential technology for future vehicular
applications. It is challenging to simultaneously achieve vehicle-to-infrastructure (V2I) and …
applications. It is challenging to simultaneously achieve vehicle-to-infrastructure (V2I) and …
Federated reinforcement learning-based resource allocation in D2D-enabled 6G
The current 5G and conceived 6G era with ultra-high density, ultra-high frequency
bandwidth, and ultra-low latency can support emerging applications like Extended Reality …
bandwidth, and ultra-low latency can support emerging applications like Extended Reality …
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