Deep Reinforcement Learning-Based Distributed Congestion Control in Cellular V2X Networks

Author:

Choi Joo-YoungORCID,Jo Han-ShinORCID,Mun CheolORCID,Yook Jong-GwanORCID

Funder

National Research Foundation of Korea

Korea Government, Ministry of Science and ICT

Korea Agency for Infrastructure Technology Advancement (KAIA) Grant

Ministry of Land, Infrastructure and Transport

MSIT, South Korea, through the Grand Information Technology Research Center Support Program

Institute for Information and communications Technology Planning and Evaluation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Cited by 25 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. AoI-Aware and Persistence-Driven Congestion Control in 5G NR - V2X Sidelink Communications;2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet);2024-06-11

2. V2X Revolution: Exploring Dynamic Resource Optimization in V2X;2024 IEEE 12th International Symposium on Signal, Image, Video and Communications (ISIVC);2024-05-21

3. Distributed Joint Congestion Control for V2X Using Multi-Agent Reinforcement Learning;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

4. SCI-Aided Resource Allocation to Improve QoS Performance of V2X Platooning Driving Service;The Journal of Korean Institute of Electromagnetic Engineering and Science;2024-04

5. Piggyback-Based Collaborative Resource Selection in C-V2X;Lecture Notes in Networks and Systems;2024

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