An Enhanced Binary Particle Swarm Optimization for Pruning Digital Predistortion Models-Reference-Cited by-同舟云学术

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An Enhanced Binary Particle Swarm Optimization for Pruning Digital Predistortion Models

Published:2024-09 Issue:9 Volume:34 Page:1119-1122
ISSN:2771-9588
Container-title:IEEE Microwave and Wireless Technology Letters
language:
Short-container-title:IEEE Microw. Wireless Tech. Lett.

Author:

Gao Kun¹^ORCID,Zhang Yufeng²,Liu Xin³^ORCID,Wang Jiewen¹,Chen Qingyue²,Shi Xu⁴,Chen Wenhua²^ORCID,Feng Haigang¹^ORCID,Feng Zhenghe²^ORCID,Ghannouchi Fadhel M.⁵^ORCID

Affiliation:

1. Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. Department of Electronic Engineering, Tsinghua University, Beijing, China

3. School of Microelectronics, Xidian University, Xi’an, China

4. Gaxtrem Technology Company Ltd., Suzhou, China

5. Intelligent RF Radio Laboratory (iRadio Lab), University of Calgary, Calgary, AB, Canada

Funder

National Key Research and Development Program of China

National Science Fund for Distinguished Young Scholars

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/9944983/10666874/10595460.pdf?arnumber=10595460

Reference13 articles.

1. Behavioral modeling and predistortion

2. A Robust Digital Baseband Predistorter Constructed Using Memory Polynomials

3. A Generalized Memory Polynomial Model for Digital Predistortion of RF Power Amplifiers

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

5. An iterative pruning of 2-D digital predistortion model based on normalized polynomial terms

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