摘要
移动通信应用场景逐渐呈现复杂化和多变化趋势,很难有一种普适性传输波形满足所有通信需求,这对多种波形的配合与协作提出了较高的要求。该文提出一种适用于复杂场景下的智能化多载波波形调制系统,发送端可通过波形激活因子选择产生合适的传输波形,接收端将不同波形信号的I/Q分量作为自适应因子,使用主成分分析法处理数据后送入智能波形识别网络(IWR-Net)完成信号的识别。所提系统融合深度学习网络,具有较为统一的硬件架构。仿真结果表明,所提方案在5G多场景下对不同发送波形识别准确率最高可达98.2%,并且在不同测试环境中具有良好的泛化性能。
Mobile communication applications scenarios are becoming complexity and diversity.It is difficult to have a universal transmission waveform to meet all communication needs,which puts forward high requirements for the coordination and collaboration of multiple waveforms.In this paper,an intelligent multicarrier waveform modulation system is proposed for complex scenarios,the sending end can select a suitable transmission waveform by the waveform activation factor,the receiving end will take the I/Q component of different waveform signals as an adaptive factor,and use the main component analysis method to process the data and feed it into the Intelligent Waveform Recognition Network(IWR-Net)to complete the identification of the signal.The proposed system is integrated with deep learning network and has a more unified hardware architecture.The simulation results show that the accuracy of different send waveform recognition can be as high as 98.2%in 5G multi-scenes,and it has good generalization performance in different test environments.
作者
邵凯
付旭阳
王光宇
SHAO Kai;FU Xuyang;WANG Guangyu(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Chongqing Key Laboratory of Mobile Communications Technology,Chongqing 400065,China;Engineering Research Center of Mobile Communications,Ministry of Education,Chongqing 400065,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2021年第11期3096-3104,共9页
Journal of Electronics & Information Technology
关键词
智能化多载波波形调制系统
多载波波形识别
深度学习
智能波形识别网络
Intelligent multi-carrier waveform modulation system
Multi-carrier waveform recognition
Deep learning
Intelligent Waveform Recognition Networks(IWR-Net)
