Wireless Channel Scenario Identification Using Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Wireless Channel Scenario Identification Using Convolutional Neural Networks

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
language:
Short-container-title:

Author:

Gopal Govind R.¹,Chen Jie²,Hillery William J.²,Tan Jun²,Özen Serdar²,Zhu Qiping³

Affiliation:

1. University of California San Diego,Department of Electrical and Computer Engineering,La Jolla,CA,USA,92093

2. Nokia of America Corporation,Nokia Standards,Naperville,IL,USA,60563

3. Intel Corporation,Next Generation and Standards,Santa Clara,CA,USA,95054

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199114/10199145/10200552.pdf?arnumber=10200552

Reference21 articles.

1. Wireless Channel Scene Recognition Method Based on an Autocorrelation Function and Deep Learning

2. Multi-Feature Fusion Based Recognition and Relevance Analysis of Propagation Scenes for High-Speed Railway Channels

3. Wireless Channel Scenario Recognition Based on Neural Networks

4. Channel Sounding and Scene Classification of Indoor 6G Millimeter Wave Channel Based on Machine Learning

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