Blind Signal Digital Modulation Classification through k-medoids Clustering

Gaurav Jajoo, Y. Yadav, S. K. Yadav
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引用次数: 7

Abstract

Modulation scheme classifier for the received RF signal is proposed in this paper. Modulation classification is an intermediate step between data detection and its demodulation for extracting the final information. Proposed method estimates the carrier frequency offset after downconversion of passband signal with estimated carrier frequency and corrects for it. Signal is sampled with high frequency and symbol rate is estimated. Sampled signal is downsampled to estimated symbol rate to extract the constellation points. For identification of modulation scheme between QAM and PSK of different orders, k-medoids clustering is used. Blindly, k medoids are estimated for k equals to 4, 8, 16 and 64 and similarity to ideal constellation structure is calculated. Final decision for modulation scheme is given in favor for which similarity with ideal constellation structure is maximum. The simulation results for the method shows that different modulation schemes are classified efficiently above 10 dB SNR in presence of Additive White Gaussian Noise. Method proposed is unsupervised and has low computational complexity.
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基于k-介质聚类的盲信号数字调制分类
对接收到的射频信号提出了调制方案分类器。调制分类是数据检测和解调之间的中间步骤,用于提取最终信息。该方法利用估计的载波频率估计通带信号下变频后的载波频偏,并对其进行校正。对信号进行高频采样,估计符号率。将采样信号降采样到估计的符号率,提取星座点。为了识别不同阶的QAM和PSK之间的调制方案,采用了k-介质聚类方法。在k = 4、8、16和64时,盲估计k个媒质,计算与理想星座结构的相似度。最后给出了与理想星座结构相似度最大的调制方案。仿真结果表明,在加性高斯白噪声存在的情况下,该方法能有效地分类出信噪比在10 dB以上的不同调制方案。该方法是无监督的,计算复杂度低。
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