Cellular System Identification Using Deep Learning: GSM, UMTS and LTE

Khalid Alshathri, Hongtao Xia, V. Lawrence, Yu-dong Yao
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引用次数: 18

Abstract

Deep learning (DL) is an effective tool in artificial intelligence (AI), especially in image based and human behavior recognition applications. However, there are many applications that are not very well explored using the DL tools. The telecommunications and networking applications are among those applications that can be explored more extensively using DL. In this paper, the neural network is utilized to identify different cellular communications signals including GSM, UMTS, and LTE. Our study results show that the cellular system identification method achieves very good identification performance without any necessity to select signal features manually.
深度学习(DL)是人工智能(AI)的有效工具,特别是在基于图像和人类行为识别应用中。然而,有许多应用程序并没有很好地利用深度学习工具进行探索。电信和网络应用是可以使用DL进行更广泛探索的应用之一。在本文中,神经网络被用于识别不同的蜂窝通信信号,包括GSM, UMTS和LTE。我们的研究结果表明,蜂窝系统识别方法在不需要手动选择信号特征的情况下取得了很好的识别性能。
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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