RFSoC Modulation Classification With Streaming CNN: Data Set Generation & Quantized-Aware Training

RFSoC Modulation Classification With Streaming CNN: Data Set Generation & Quantized-Aware Training

This paper introduces a novel FPGA-based Convolutional Neural Network (CNN) architecture for continuous radio data processing, specifically targeting modulation classification on the Zynq UltraScale+ Radio Frequency System on Chip (RFSoC) operating in real-time. Evaluated on AMD’s RFSoC2x...

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Bibliographic Details
Main Authors: Andrew Maclellan, Louise H. Crockett, Robert W. Stewart
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Circuits and Systems
Subjects:
Deep learning (DL)
wireless communications
AMD
FPGA
RFSoC
PYNQ
Online Access:https://ieeexplore.ieee.org/document/10772713/
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https://ieeexplore.ieee.org/document/10772713/

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