相位:一种基于随机森林的自动调制分类系统

2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2017-03-06 DOI:10.1109/DySPAN.2017.7920749

Kostis Triantafyllakis, M. Surligas, George Vardakis, Stefanos Papadakis

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引用次数: 20

摘要

我们提出了一个包含自动调制分类(AMC)机制的架构，并辅以随机森林机器学习(ML)分类器。使用这种架构，我们能够在各种信噪比环境下区分各种数字和模拟调制方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Phasma: An automatic modulation classification system based on Random Forest

We propose an architecture that incorporates an automatic modulation classification (AMC) mechanism, assisted by Random Forest machine learning (ML) classifiers. Using this architecture we are able to distinguish a variety of digital and analog modulation schemes under various SNR environments.

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2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)

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