脉冲噪声下基于平滑循环相关熵谱的调制识别方法

Pol-CCES based modulation recognition method under impulsive noise

针对脉冲噪声下的信号分类问题,提出了基于平滑循环相关熵谱和浅层残差网络的调制识别方案。所提方案不仅具有较低的计算复杂度,而且在脉冲噪声环境中具有稳健性。仿真实验表明,即使在很低的广义信噪比下,所提方案依然具有良好的性能。

To realize signal classification in impulsive noise environment,a modulation recognition scheme based on polished cyclic correntropy spectrum and shallow residual network was proposed.The proposed scheme not only has low computational complexity but also shows robustness to impulsive noise.Simulation results demonstrate the proposed solution’s superior performance under impulsive noise,even when the generalized signal-to-noise ratio is very low.