A Reinforcement Learning Framework for PQoS in a Teleoperated Driving Scenario-Reference-Cited by-同舟云学术

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A Reinforcement Learning Framework for PQoS in a Teleoperated Driving Scenario

Published:2022-04-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Wireless Communications and Networking Conference (WCNC)
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Author:

Mason Federico¹,Drago Matteo¹,Zugno Tommaso²,Giordani Marco¹,Boban Mate²,Zorzi Michele¹

Affiliation:

1. University of Padova,Department of Information Engineering,Italy

2. Huawei Technologies,Munich Research Center,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9771381/9771540/09771590.pdf?arnumber=9771590

Cited by 5 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. Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies;2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring);2023-06

2. Towards AI-Native Vehicular Communications;2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring);2023-06

3. Simulation of Tele-Operated Driving over 5G Using CARLA and OMNeT++;2023 IEEE Vehicular Networking Conference (VNC);2023-04-26

4. Predictive Quality of Service in Cellular Networks: Challenges, Framework, and Application in Vehicular Communications;IEEE Communications Magazine;2023-03

5. Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3;Proceedings of the WNS3 2022;2022-06-22

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