基于机器学习的室内/室外蜂窝网络客户端分类技术

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) Pub Date : 2020-01-01 DOI:10.1109/CCNC46108.2020.9045473

Kareem Abdullah, Sara A. Attalla, Y. Gadallah, A. Elezabi, Karim G. Seddik, Ayman Gaber, Dina, Samak

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引用次数: 5

摘要

在本文中，我们提出了一种基于机器学习的蜂窝系统室内/室外(IO)用户分类算法，适用于3G网络。我们考虑不同的场景。实验结果表明，IO分类的最佳机器学习算法是boosting算法，准确率达到88.9%。

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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A Machine Learning-Based Technique for the Classification of Indoor/Outdoor Cellular Network Clients

In this paper, we propose a machine learning-based indoor/outdoor (IO) user classification algorithm in cellular systems as pertains to 3G networks. We consider different scenarios. The experimental results show that the best machine learning algorithm for IO classification is the boosting algorithm with an accuracy that reaches 88.9%.

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来源期刊

2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC)

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