Federated Deep Reinforcement Learning-Based Spectrum Access Algorithm With Warranty Contract in Intelligent Transportation Systems-Reference-Cited by-同舟云学术

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Federated Deep Reinforcement Learning-Based Spectrum Access Algorithm With Warranty Contract in Intelligent Transportation Systems

Published:2023-01 Issue:1 Volume:24 Page:1178-1190
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Zhu Rongbo¹^ORCID,Li Mengyao²,Liu Hao²^ORCID,Liu Lu³^ORCID,Ma Maode⁴^ORCID

Affiliation:

1. College of Informatics, Huazhong Agricultural University, Wuhan, China

2. College of Computer Science, South-Central University for Nationalities, Wuhan, China

3. School of Informatics, University of Leicester, Leicester, U.K.

4. College of Engineering, Qatar University, Doha, Qatar

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10026638/09800975.pdf?arnumber=9800975

Reference48 articles.

1. An overview of deep reinforcement learning for spectrum sensing in cognitive radio networks

2. Deep Q-Learning with Multiband Sensing for Dynamic Spectrum Access

3. Reinforcement and deep reinforcement learning for wireless Internet of Things: A survey

4. Reinforcement-Learning-Based Resource Allocation for Energy-Harvesting-Aided D2D Communications in IoT Networks

5. Q-Learning-Based Spectrum Access for Multimedia Transmission Over Cognitive Radio Networks

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1. Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing;IEEE Transactions on Intelligent Transportation Systems;2024-07

2. Deep Reinforcement Learning-Based Adaptive Computation Offloading and Power Allocation in Vehicular Edge Computing Networks;IEEE Transactions on Intelligent Transportation Systems;2024

3. 1-D Convolutional Neural Network-Based Models for Cooperative Spectrum Sensing;Future Internet;2023-12-29

4. Federated Reinforcement Learning in IoT: Applications, Opportunities and Open Challenges;Applied Sciences;2023-05-26

5. Guest Editorial Introduction to the Special Issue on Cognitive Networking for Intelligent Transportation Systems;IEEE Transactions on Intelligent Transportation Systems;2023-01

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