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Modulation Recognition of Radio Signals Based on Edge Computing and Convolutional Neural Network 被引量:2
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作者 Jiyu Jiao Xuehong Sun +4 位作者 Yanpeng Zhang Liping Liu Jianfeng Shao Jiafeng Lyu Liang Fang 《Journal of Communications and Information Networks》 CSCD 2021年第3期280-300,共21页
Software defined radio(SDR)is a wireless communication technology that uses modern software to control the traditional“pure hardware circuit”.It can provide an effective and secure solution to the problem of buildin... Software defined radio(SDR)is a wireless communication technology that uses modern software to control the traditional“pure hardware circuit”.It can provide an effective and secure solution to the problem of building multi-mode,multi-frequency and multifunction wireless communication equipment.Although the concept and application of SDR have been studied a lot,there is little discussion about the operating efficiency of the established system.For the purpose of shortening the delay of mapping and reducing the high computing load in the cloud,a radio monitoring system based on edge computing is developed to achieve the flexible,extensible and real-time monitoring of high-performance SDR applications.To promote the edge intelligence of deep learning(DL)service deployment through edge computing(EC),we developed an edge intelligence algorithm of convolutional neural network(CNN)based on attention mechanism to carry out modulation recognition(MR)of the edge signal and make MR closer to the antenna terminal.Through the experiment of the system and the edge algorithm,this thesis verifies the effectiveness of the developed multifunction radio signal monitoring system. 展开更多
关键词 edge computing software-defined radio cognitive radio USRP energy perception modulation recognition convolutional neural network frequencyhopping recognition
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