西安电子科技大学学报（自然科学版）2024，Vol.51Issue(4)：78-90,13.DOI:10.19665/j.issn1001-2400.20240312
基于二维异步同相正交直方图的调制方式识别
Modulation recognition based on the two-dimensional asynchronous in-phase quadrature histogram
摘要
Abstract
Automatic modulation recognition technology accurately identifies the modulation type of signals,making it a key technology in the field of signal processing.Traditional recognition methods suffer from low accuracy at low signal-to-noise ratios,and performance degradation or failure when dealing with signal frequency instability or asynchronous sampling.In this paper,we investigate modulation recognition technology based on deep learning for low-speed asynchronous sampled signals under channel conditions with varying signal-to-noise ratios and delays.We start by modeling low-speed asynchronous sampled signals and generating a two-dimensional asynchronous in-phase quadrature histogram using their in-phase and quadrature components.Subsequently,we employ a Radial Basis Function Neural Network to extract feature parameters from this two-dimensional image,thus achieving modulation type recognition for the input signal.Extensive computer simulations validate the proposed method's accuracy in recognizing seven modulation types under the influence of additive white Gaussian noise.Experimental results demonstrate that,in the presence of additive white Gaussian noise in the channel model and with an input signal-to-noise ratio of 6 dB,the average recognition accuracy can exceed 95% .Comparative experiments further verify the effectiveness and robustness of the proposed approach.关键词
调制方式识别/二维异步同相正交直方图/深度学习/径向基神经网络Key words
modulation recognition/two-dimensional asynchronous in-phase quadrature histogram/deep learning/radial basis function neural network分类
信息技术与安全科学引用本文复制引用
万鹏武,惠茜,陈东瑞,吴波..基于二维异步同相正交直方图的调制方式识别[J].西安电子科技大学学报（自然科学版）,2024,51(4):78-90,13.基金项目
国家自然科学基金(62101441) （62101441）
重点实验室基金资助项目2022-JCJQ-LB-006(6142411222203) （6142411222203）
