计算机应用与软件2024，Vol.41Issue(5)：113-117,5.DOI:10.3969/j.issn.1000-386x.2024.05.018
低过采样数字调制信号的多尺度一维卷积神经网络解调器
MULTI-SACLE 1D-CNN DEMODULATOR FOR LOW OVERSAMPLING DIGITAL MODULATION SIGNAL
摘要
Abstract
Aiming at the problem of high oversampling requirements when applying deep learning methods to demodulate of digital modulation signals,this paper designs a multi-scale one-dimensional convolutional neural network digital demodulator with low oversampling.It could demodulate the four digital modulation signals of BPSK,4-QAM,8-QAM,and 16-QAM under the same oversampling conditions as the traditional demodulator,and could ensure the same error performance of the traditional demodulation method.Simulation results show that under Gaussian and Rayleigh fading channels,the provided digital modulation signal demodulator can not only ensure the performance of demodulation error codes,but also reduce the requirement of sampling multiple,and also reduce the complexity of neural network structure.关键词
低采样倍数/解调/多尺度一维卷积神经网络/BPSK和M-QAMKey words
Low sampling multiple/Demodulation/Multi-sacle 1D-CNN/BPSK and M-QAM分类
信息技术与安全科学引用本文复制引用
陈显敏,符杰林..低过采样数字调制信号的多尺度一维卷积神经网络解调器[J].计算机应用与软件,2024,41(5):113-117,5.基金项目
国家自然科学基金项目(61761014). （61761014）
