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首页> 外文期刊>Journal of Telecommunications System & Management >Automatic Modulation Recognition in OFDM Systems using Cepstral Analysis and Support Vector Machines
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Automatic Modulation Recognition in OFDM Systems using Cepstral Analysis and Support Vector Machines

机译:使用倒频谱分析和支持向量机的OFDM系统自动调制识别

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This paper discusses the modulation recognition for OFDM signals in different Signal to Noise Ratio (SNR) and multipath channels. In this paper, the Mel Frequency Cepstral Coefficients (MFCCs) used for feature extraction and the Support Vector Machine (SVM) as classifier or Artificial Neural Network (ANN). Simulation results indicate that the proposed feature classifier have good performances in different SNR and multipath channels for both recognition rate and CPU time from the Artificial Neural Network (ANN), and the SVM classifier’s generalizing ability proves to be good.
机译:本文讨论了不同信噪比(SNR)和多径信道中OFDM信号的调制识别。在本文中,用于特征提取的梅尔频率倒谱系数(MFCC)和支持向量机(SVM)作为分类器或人工神经网络(ANN)。仿真结果表明,所提出的特征分类器在不同的信噪比和多径通道上,在人工神经网络(ANN)的识别率和CPU时间方面均具有良好的性能,并且证明了SVM分类器的泛化能力很好。

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