摘要
针对OFDM信号与单载波信号调制识别,提出了一种基于高阶累积量特征的改进方法.通过分析复信号幅值的归一化四阶累积量特性,以及信号的瞬时频率和功率谱特征,改进和提出新的特征参数,采用支持向量机分类器,实现了AWGN信道下包括OFDM在内的9种信号的制式自动识别.该方法具有特征参数易于提取、抗噪性好、识别准确率高的优点.利用MATLAB仿真证明在信噪比不小于7dB的情况下,OFDM信号的识别准确率达99%.
Aiming at the automatic modulation recognition of OFDM signal and Single carrier signals , this paper proposes a improved method based on high-order cumulants .By analysing the normalized fourth-order cumulant features of the complex signal amplitude ,the characteristics of instantaneous frequency and power spectrum ,new feature parameters are proposed .With support vector machine (SVM ) classifier ,the automatic identification of 9 kinds of signals including OFDM in the AWGN channel is achieved .The method has lots of advantages ,such as the feature parameters could be extracted easily and have good anti-noise performance ,and recognition accuracy rates are also very high .When SNR is not less than 7 dB ,the simulation results on MATLAB indicate that identification probability of this proposed method is 99% .
出处
《微电子学与计算机》
CSCD
北大核心
2014年第10期98-102,共5页
Microelectronics & Computer
基金
国家"八六三"计划项目(2012AA012305)
关键词
调制识别
特征参数提取
高阶累积量
支持向量机
modulation recognition
feature extraction
higher-order cumulant
support vector machine(SVM)
