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A Modular 1D-CNN Architecture for Real-time Digital Pre-distortion

This study reports a novel hardware-friendly modular architecture for implementing one dimensional convolutional neural network (1D-CNN) digital predistortion (DPD) technique to linearize RF power amplifier (PA) real-time.The modular nature of our design enables DPD system adaptation for variable re...

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Bibliographic Details
Published in:arXiv.org 2021-11
Main Authors: Udara De Silva, Koike-Akino, Toshiaki, Ma, Rui, Yamashita, Ao, Nakamizo, Hideyuki
Format: Article
Language:English
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Summary:This study reports a novel hardware-friendly modular architecture for implementing one dimensional convolutional neural network (1D-CNN) digital predistortion (DPD) technique to linearize RF power amplifier (PA) real-time.The modular nature of our design enables DPD system adaptation for variable resource and timing constraints.Our work also presents a co-simulation architecture to verify the DPD performance with an actual power amplifier hardware-in-the-loop.The experimental results with 100 MHz signals show that the proposed 1D-CNN obtains superior performance compared with other neural network architectures for real-time DPD application.
ISSN:2331-8422
DOI:10.48550/arxiv.2111.09637