  Radio signal classification has a very wide range of applications in
cognitive radio networks and electromagnetic spectrum monitoring. In this
article, we consider scenarios where multiple nodes in the network participate
in cooperative classification. We propose cooperative radio signal
classification methods based on deep learning for decision fusion, signal
fusion and feature fusion, respectively. We analyze the performance of these
methods through simulation experiments. We conclude the article with a
discussion of research challenges and open problems.
