Learning Based Multi-Channel Access in Vehicular Networks With Illegal Operators and Users-Reference-Cited by-同舟云学术

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Learning Based Multi-Channel Access in Vehicular Networks With Illegal Operators and Users

Published:2023-03 Issue:3 Volume:72 Page:4097-4102
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Li Li¹^ORCID,Li Wei¹^ORCID,Chen Xiaonan¹^ORCID,Wang Jun¹^ORCID,Peng Qihang²^ORCID

Affiliation:

1. National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Sichuan, China

2. School of Infomation and Communication Engineering, University of Electronic Science and Technology of China, Sichuan, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Sichuan Province

Sichuan Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10070114/09946429.pdf?arnumber=9946429

Reference17 articles.

1. Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks

2. Graph Coloring Based Resource Sharing (GCRS) Scheme for D2D Communications Underlaying Full-Duplex Cellular Networks

3. An analysis of deep neural network models for practical applications;canziani;Proc Comput Vis Pattern Recognit,0

4. Prioritized experience replay;schaul;Proc Int Conf Learn Representations,0

5. Continuous control with deep reinforcement learning;lillicrap;Proc Int Conf Learn Representations,0

Cited by 3 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. Robust Beamforming for Sensing Assisted Integrated Communication and Jamming Systems;IEEE Transactions on Vehicular Technology;2023-10

2. Coordinated Variable Speed Limit Control for Consecutive Bottlenecks on Freeways Using Multiagent Reinforcement Learning;Journal of Advanced Transportation;2023-06-27

3. Model-Based Deep Reinforcement Learning Framework for Channel Access in Wireless Networks;IEEE Internet of Things Journal;2023

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