Wireless Signal Service Type Identification Based on Convolutional Neural Network

Haomin Tian, Liang Yin, Xiaofeng Yang, Shufang Li, Haoyang Yu
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引用次数: 1

Abstract

Nowadays, with the birth of 5G and the Internet of Things, more and more business signals have emerged. The identification of signal service types has become a hot research topic. Whether it is suitable for daily life in the military field, there is a wide application prospect. Using the power spectrum data of the wireless signal, the characteristics of the power spectrum waveform are captured to identify the type of traffic of the wireless signal. This paper proposes the use of convolutional neural networks to extract and classify the wireless signal power spectrum data. After hundreds of iterative training, it can achieve an ideal recognition effect.
基于卷积神经网络的无线信号业务类型识别
如今,随着5G和物联网的诞生,越来越多的商业信号出现了。信号业务类型的识别已成为一个研究热点。是否适用于日常生活中的军事领域,都有着广阔的应用前景。利用无线信号的功率谱数据,捕获功率谱波形的特征来识别无线信号的流量类型。本文提出利用卷积神经网络对无线信号功率谱数据进行提取和分类。经过数百次迭代训练,可以达到理想的识别效果。
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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