A Residual Selectable Modeling Method Based on Deep Neural Network for Power Amplifiers With Multiple States-Reference-Cited by-同舟云学术

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A Residual Selectable Modeling Method Based on Deep Neural Network for Power Amplifiers With Multiple States

Published:2024-08 Issue:8 Volume:34 Page:1043-1046
ISSN:2771-9588
Container-title:IEEE Microwave and Wireless Technology Letters
language:
Short-container-title:IEEE Microw. Wireless Tech. Lett.

Author:

Chang Zongyu¹,Hu Xin¹^ORCID,Li Boyan¹^ORCID,Yao Quanhao¹,Yao Yurong¹,Wang Weidong¹^ORCID,Ghannouchi Fadhel M.²^ORCID

Affiliation:

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

2. Department of Electrical and Computer Engineering, Schulish School of Engineering, Intelligent RF Radio Laboratory, University of Calgary, Calgary, AB, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/9944983/10631739/10587151.pdf?arnumber=10587151

Reference14 articles.

1. Behavioral modeling and predistortion

2. Receiver-Assisted Nonlinear Compensation of Power Amplifier for PD-NOMA

3. A Low Running Complexity Model for Digital Predistortion of RF Power Amplifiers

4. Convolutional Neural Network for Behavioral Modeling and Predistortion of Wideband Power Amplifiers

5. Power adaptive digital predistortion for RF power amplifiers

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