Modulation Format Identification Based on Channel-spatial Attention Modules and Deep Learning

In this paper, a scheme is proposed where the channel and spatial attention convolutional neural networks are applied to identify modulation formats from signal constellation diagrams. According to the simulation results, it outperforms other modulation format identification (MFI) schemes in the overall identification rate. Moreover, the scheme shows a significant advantage in signal identification given low optical signal-to-noise ratios (OSNRs).