脉冲噪声下基于平滑循环相关熵谱的调制识别方法

doi:10.11959/j.issn.1000-436x.2021231

通信学报 ›› 2021, Vol. 42 ›› Issue (12): 121-133.doi: 10.11959/j.issn.1000-436x.2021231

脉冲噪声下基于平滑循环相关熵谱的调制识别方法

戴江安¹, 栾声扬², 赵明龙², 张兆军², 邱天爽¹

¹ 大连理工大学电子信息与电气工程学部，辽宁大连 116024
² 江苏师范大学电气工程及自动化学院，江苏徐州 221116

修回日期:2021-11-29 出版日期:2021-12-01 发布日期:2021-12-01
作者简介:戴江安（1991- ），男，江西抚州人，大连理工大学博士生，主要研究方向为波达方向估计、调制识别等
栾声扬（1983- ），男，辽宁大连人，博士，江苏师范大学讲师，主要研究方向为无线电信号处理、人工智能技术等
赵明龙（1992- ），男，安徽阜阳人，江苏师范大学硕士生，主要研究方向为深度学习和信号处理
张兆军（1981- ），男，山东枣庄人，博士，江苏师范大学副教授，主要研究方向为机器学习、群体智能等
邱天爽（1954- ），男，江苏海门人，博士，大连理工大学教授，主要研究方向为非高斯非平稳随机信号处理
基金资助:
国家自然科学基金资助项目(61671105);国家自然科学基金资助项目(61801197)

Pol-CCES based modulation recognition method under impulsive noise

Jiang’an DAI¹, Shengyang LUAN², Minglong ZHAO², Zhaojun ZHANG², Tianshuang QIU¹

¹ Faculty of Electronic Information and Electrical Engineering， Dalian University of Technology， Dalian 116024， China
² School of Electrical Engineering and Automation， Jiangsu Normal University， Xuzhou 221116， China

Revised:2021-11-29 Online:2021-12-01 Published:2021-12-01
Supported by:
The National Natural Science Foundation of China(61671105);The National Natural Science Foundation of China(61801197)

摘要/Abstract

摘要：

针对脉冲噪声下的信号分类问题，提出了基于平滑循环相关熵谱和浅层残差网络的调制识别方案。所提方案不仅具有较低的计算复杂度，而且在脉冲噪声环境中具有稳健性。仿真实验表明，即使在很低的广义信噪比下，所提方案依然具有良好的性能。

关键词: 调制识别, 脉冲噪声, 平滑循环相关熵谱, 浅层残差网络

Abstract:

To realize signal classification in impulsive noise environment， a modulation recognition scheme based on polished cyclic correntropy spectrum and shallow residual network was proposed.The proposed scheme not only has low computational complexity but also shows robustness to impulsive noise.Simulation results demonstrate the proposed solution’s superior performance under impulsive noise， even when the generalized signal-to-noise ratio is very low.

Key words: modulation recognition, impulsive noise, polished cyclic correntropy spectrum, shallow residual network

中图分类号:

TN911.7

戴江安, 栾声扬, 赵明龙, 张兆军, 邱天爽. 脉冲噪声下基于平滑循环相关熵谱的调制识别方法[J]. 通信学报, 2021, 42(12): 121-133.

Jiang’an DAI, Shengyang LUAN, Minglong ZHAO, Zhaojun ZHANG, Tianshuang QIU. Pol-CCES based modulation recognition method under impulsive noise[J]. Journal on Communications, 2021, 42(12): 121-133.

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网络深度	FLOPs
本文网络	0.14×10 ⁹
18层	1.8×10 ⁹
34层	3.6×10 ⁹
50层	3.8×10 ⁹
101层	7.6×10 ⁹
152层	11.3×10 ⁹

参数	实验1	实验2
GSNR/dB	[-5， 15]	5
α值	1.3	[1.0， 2.0]
星座图	—	—
FLOCS	p= 1.2	p= 1.2
Log-CCES	σ= 0.3	σ= 0.3
Pol-CCES	σ= 0.3	σ= 0.3

脉冲噪声下基于平滑循环相关熵谱的调制识别方法

Pol-CCES based modulation recognition method under impulsive noise

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