Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems-Reference-Cited by-同舟云学术

Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
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Author:

Vu Hung V.¹,Farzanullah Mohammad²,Liu Zheyu²,Nguyen Duy H. N.³,Morawski Robert²,Le-Ngoc Tho²

Affiliation:

1. Huawei Technologies Canada,Ottawa,ON,Canada

2. McGill University,Department of Electrical & Computer Engineering,Montreal,QC,Canada

3. San Diego State University,Department of Electrical & Computer Engineering,CA,USA

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860273/9860350/09860518.pdf?arnumber=9860518

Reference13 articles.

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2. Deep Reinforcement Learning with Double Q-Learning

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4. 3rd generation partnership project; Technical specification group radio access network; Study LTE-based V2X services (Release 14);TR 36 885 V2 0 0,2016

5. Interference Graph-Based Resource-Sharing Schemes for Vehicular Networks

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