WaveNet: Toward Waveform Classification in Integrated Radar–Communication Systems With Improved Accuracy and Reduced Complexity-Reference-Cited by-同舟云学术

WaveNet: Toward Waveform Classification in Integrated Radar–Communication Systems With Improved Accuracy and Reduced Complexity

Published:2024-07-15 Issue:14 Volume:11 Page:25111-25123
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Huynh-The Thien¹^ORCID,Hoang Van-Phuc²^ORCID,Kim Jae-Woo³^ORCID,Le Minh-Thanh¹,Zeng Ming⁴^ORCID

Affiliation:

1. Department of Computer and Communications Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam

2. Institute of System Integration, Le Quy Don Technical University, Hanoi, Vietnam

3. ICT Convergence Research Center and the Department of IT Convergence, Kumoh National Institute of Technology, Gumi, Gyeongsangbuk, Republic of Korea

4. Department of Electric and Computer Engineering, Laval University, Québec City, QC, Canada

Funder

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Postdoctoral Scholarship Programme of Vingroup Innovation Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10589449/10506215.pdf?arnumber=10506215

Reference44 articles.

1. GS-QRNN: A High-Efficiency Automatic Modulation Classifier for Cognitive Radio IoT

2. AI-Driven Blind Signature Classification for IoT Connectivity: A Deep Learning Approach

3. CNN Based Target Classification in Vehicular Networks with Millimeter-Wave Radar

4. Joint OAM Radar-Communication Systems: Target Recognition and Beam Optimization

5. Reliability and Security of CR-STAR-RIS-NOMA Assisted IoT Networks

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