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基于多重分形特征的通信调制方式识别研究
引用本文:陈红,蔡晓霞,徐云,刘文涛.基于多重分形特征的通信调制方式识别研究[J].电子与信息学报,2016,38(4):863-869.
作者姓名:陈红  蔡晓霞  徐云  刘文涛
作者单位:1.(解放军电子工程学院 合肥 230037) ②(解放军95915部队 天津 301612)
基金项目:国家自然科学基金(61571446),安徽省自然科学基金(KY13C152)
摘    要:该文提出一种基于多重分形特征的数字通信信号调制方式识别新方法。对接收信号进行去噪预处理,基于2维数据阵列求取信号的广义维数和多重分形谱;详细讨论了权重因子q对多重分形谱的影响,提取了13个多重分形特征参数;设计了基于多重分形特征的支持向量机分类器对不同信号进行调制方式识别。仿真结果表明,该算法在低信噪比情况下具有很好的识别性能。

关 键 词:调制方式识别    多重分形特征    广义维数    支持向量机
收稿时间:2015-06-08

Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics
CHEN Hong,CAI Xiaoxia,XU Yun,LIU Wentao.Communication Modulation Recognition Based on Multi-fractal Dimension Characteristics[J].Journal of Electronics & Information Technology,2016,38(4):863-869.
Authors:CHEN Hong  CAI Xiaoxia  XU Yun  LIU Wentao
Affiliation:1.(PLA Electronic Engineering Institute, Hefei 230037, China)2.(Unit 95915 of PLA, Tianjin 301612, China)
Abstract:A new modulation recognition algorithm of digital communication signals based on the multi-fractal dimension characteristics is proposed. Employing preprocessing the received signal, the generalized dimension and the multi-fractal spectrum can be calculated by 2D data array. The effect of multi-fractal spectrum due to the weighted factorsq is discussed in detail, the 13 multi-fractal characteristic parameters are extracted. The Support Vector Machine (SVM) classifier based on the multi-fractal dimension characteristics is designed for recognition of different modulation signals. Simulation results show that the proposed method has a good recognition performance under low SNR.
Keywords:
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