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Energy-Efficient Channel Switching in Cognitive Radio Networks: A Reinforcement Learning Approach

  • Published:2020-10 Issue:10 Volume:69 Page:12359-12362
  • ISSN:0018-9545
  • Container-title:IEEE Transactions on Vehicular Technology
  • language:
  • Short-container-title:IEEE Trans. Veh. Technol.

Author:

Ding HaichuanORCID,Li XuanhengORCID,Ma YingORCID,Fang YuguangORCID

Funder

National Science Foundation

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Doctoral Research Initiation Fund of Liaoning Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Cited by 15 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. Enhanced deep learning-based optimization model for the optimal energy efficiency-oriented Cognitive Radio Networks;Ain Shams Engineering Journal;2024-09

2. RF-CVN: Recurrent Reinforcement Learning Framework for Cognitive Vehicular Ad-Hoc Networks Routing;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

3. Deadline-Constrained Opportunistic Spectrum Access with Spectrum Handoff;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

4. Intelligent Cloud-Edge Collaborations Assisted Energy-Efficient Power Control in Heterogeneous Networks;IEEE Transactions on Wireless Communications;2023-11

5. To study about various existing schemes in this field of cloud enabled cognitive radio environment;2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS);2023-10-27
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