Automatic Modulation Classification in Impulsive Noise: Log-Domain 3-D Constellation Diagrams and Multiscale Dual-Convolutional 3DCNN-Reference-Cited by-同舟云学术

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Automatic Modulation Classification in Impulsive Noise: Log-Domain 3-D Constellation Diagrams and Multiscale Dual-Convolutional 3DCNN

Published:2024-08 Issue:4 Volume:10 Page:1204-1217
ISSN:2332-7731
Container-title:IEEE Transactions on Cognitive Communications and Networking
language:
Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

Bai Jiansheng¹^ORCID,Yao Jinjie¹^ORCID,Guo Yurong¹,Yang Zhiliang¹,Wang Liming¹^ORCID

Affiliation:

1. State Key Laboratory for Electronic Testing Technology, North University of China, Taiyuan, Shanxi, China

Funder

National Key Research and Development Program of China

Shanxi Provincial Key Research and Development Project

Natural Science Foundation of Shanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6687307/10629642/10466381.pdf?arnumber=10466381

Reference38 articles.

1. Polarization Channel Estimation for Circular and Non-Circular Signals in Massive MIMO Systems

2. Image-Like Situational Difference Mapping (ILSDM)-Based Method for Detecting Anomalies in Electromagnetic Environment

3. A Novel Deep Learning and Polar Transformation Framework for an Adaptive Automatic Modulation Classification

4. Automatic Modulation Classification: A Deep Learning Enabled Approach

5. Automatic Modulation Classification Based on Decentralized Learning and Ensemble Learning

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