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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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Published in: | arXiv.org 2021-11 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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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. |
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ISSN: | 2331-8422 |
DOI: | 10.48550/arxiv.2111.09637 |