Modulation Classification Using Neural Networks

In this paper we explore the performance of neural network based modulation classification systems, specifically the convolutional neural network (CNN) and the residual neural network (ResNet). Using the PyTorch machine learning library, we are able to get comparable results reported by other researchers using different frameworks. We also explore the effects that frequency offset and frame boundary misalignment have on the results.