Deep Reinforcement Learning based Congestion Control for V2X Communication
Author:
Affiliation:
1. Fraunhofer IIS,Erlangen,Germany
2. Robert Bosch GmbH,Germany
3. Friedrich Alexander University,Erlangen-Nürnberg,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9569244/9569245/09569259.pdf?arnumber=9569259
Cited by 12 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
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3. A Deep Reinforcement Learning Approach for Adaptive Traffic Routing in Next-Gen Networks;ICC 2024 - IEEE International Conference on Communications;2024-06-09
4. Enhancing Sidelink 5G V2V Communication: A Distributed Probabilistic Congestion Control for Dynamic Resource Allocation;2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS);2023-12-17
5. Deep reinforcement learning‐based dual‐mode congestion control for cellular V2X environments;Electronics Letters;2023-10
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