Deep Reinforcement Learning Based Hopping Strategy for Wideband Anti-Jamming Wireless Communications-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning Based Hopping Strategy for Wideband Anti-Jamming Wireless Communications

Published:2023 Issue: Volume: Page:1-12
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Qi Jie¹,Zhang Hongming¹^ORCID,Qi Xiaolei²^ORCID,Peng Mugen²^ORCID

Affiliation:

1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

2. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China

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/ielx7/25/4356907/10287624.pdf?arnumber=10287624

Cited by 4 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. Intelligent decision-making for a “Three-Variable” frequency-hopping pattern based on OC-CDRL;Physical Communication;2024-10

2. A novel intelligent anti-jamming communication algorithm based on proximal policy optimization;Physical Communication;2024-08

3. Joint Intelligent Reflecting Surface-Aided Frequency-Hopping Anti-Jamming for Tactical Wireless Systems;ICC 2024 - IEEE International Conference on Communications;2024-06-09

4. Anti-Jamming Strategy Based on Reinforcement Learning with Sequence Information;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19

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