Classification of Single- and Multi-carrier Signals Using CNN Based Deep Learning-Reference-Cited by-同舟云学术

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Classification of Single- and Multi-carrier Signals Using CNN Based Deep Learning

Published:2021-11-17 Issue: Volume: Page:
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Container-title:2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)
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Author:

An Sungbae,Jang Mingyu,Yoon Dongweon

Funder

Institute for Information & communications Technology Promotion (IITP)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9660393/9660398/09660515.pdf?arnumber=9660515

Reference17 articles.

1. Iterative Blind OFDM Parameter Estimation and Synchronization for Cognitive Radio Systems

2. Blind Modulation Classification for Asynchronous OFDM Systems Over Unknown Signal Parameters and Channel Statistics

3. Deep Learning-Based Automatic Modulation Recognition Method in the Presence of Phase Offset

4. OFDM Modulation Classification and Parameters Extraction

5. Fourth order cumulants in distinguishing single carrier from OFDM signals

Cited by 2 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. Multicarrier Waveforms Classification with LDA and CNN for 5G;Communications in Computer and Information Science;2023-11-05

2. A multi-task learning model for non-intrusive load monitoring based on discrete wavelet transform;The Journal of Supercomputing;2023-01-06

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