计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 79-82.

• 计算机网络与信息安全 • 上一篇    下一篇

数字调制信号识别的特征参数优化方法

刘明骞,李兵兵,赵雷   

  1. (西安电子科技大学综合业务网理论与关键技术国家重点实验室 西安710071)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家“863”高技术研究发展计划项目(2007AA01Z288 ),国家自然科学基金项目(60772138),高等学校学科创新引智计划项目(808038)资助。

Feature Optimization for Digital Modulation Signals Recognition

LIU Ming-qian,Li Bing-bing,ZAHO Lei   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对数字调制信号识别中特征参数数目多和特征冗余的问题,提出一种数字调制信号识别的特征参数优化方法。首先利用正交实验对常用的20个特征参数进行优化选择,然后利用RI3F神经网络识别9种数字调制信号,最后分别与主分量分析方法((PCA)和核主分量分析方法(KPCA)进行比较。仿真结果表明,该方法在高斯和多径信道下均能够有效地对特征参数进行优化选择,比PCA方法和KPCA方法有更好的优化能力。

关键词: 调制识别,特征参数选择,正交实验,主分量分析,核主分量分析

Abstract: Aiming at the problem of feature parameter numerousness and feature redundancy in the recognition of digital modulation signals, a feature optimization method for digital modulation signals recognition was proposed in this paper.Firstly,the method optimized the feature parameters of twenty selected features by orthogonal experiment And then it recognized nine kinds of digital modulation signals using RI3F neural network. Finally, the method compared to PCA method and KPCA method. The simulation results show that the method is able to optimize feature parameters effeclively in Gaussian and multipath channel,and has much better optimization ability than PC八and KPCA methods.

Key words: Modulation recognition, Feature parameter selection, Orthogonal design experiment, PCA, KPCA

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