In this paper, we propose a novel low-complexity scheme to extract cyclic features of wideband signals from sub-Nyquist samples as Nyquist rates push contemporary analog-to-digital converters to their performance limits. Due to the sparse spectrum occupancy in wideband, sub-Nyquist sampling is performed and cyclostationary feature extraction is achieved at baseband to identify the modulation scheme with low computational complexity. The multichannel sub-Nyquist sampling structure of the modulated wideband converter (MWC) is used to perform spectrum sensing. Automatic modulation identification and classification are done based on cyclostationary feature detection for the efficient use of available spectrum bands. The computational complexity is reduced as the aliased copy of the signal in baseband obtained in each channel of MWC is only used to estimate the cyclic spectrum of the signal and identify the modulation scheme. Simulations performed validate the proposed method for various modulation schemes.

在本文中，我们提出了一种新的低复杂度方案，从亚奈奎斯特样本中提取宽带信号的循环特征，因为奈奎斯特速率将当代模数转换器推向其性能极限。由于宽带频谱占用稀疏，在基带进行亚奈奎斯特采样并实现循环平稳特征提取，以识别低计算复杂度的调制方案。调制宽带转换器 (MWC) 的多通道亚奈奎斯特采样结构用于执行频谱感知。自动调制识别和分类是基于循环平稳特征检测完成的，以有效利用可用频谱带。由于在MWC的每个通道中获得的基带信号的混叠副本仅用于估计信号的循环谱和识别调制方案，因此计算复杂度降低。执行的模拟验证了针对各种调制方案的建议方法。