Modes recognition algorithm of vortex beam based on simple parameter-free attention convolutional neural networks
When vortex beam propagates in the atmosphere,phase distortion is generated due to the influence of atmospheric turbulence,which makes it difficult to detect the mode at the receiving end and reduces the reliability of the communication system.In order to improve the accuracy of vortex beam mode recognition,a simple parameter-free attention convolution neural network(S-ConvNeXt)is proposed.Results show that this proposed network can effectively focus on key bright spot features.When the transmission distance is 2 km,the accuracy of eigenstate recognition can reach 100%,98.8%,96.4%,89.7%,the accuracy of superposition state recognition can reach 100%,99.8%,98.8%,96.5%,via weak turbulence,medium turbulence,strong turbulence and stronger turbulence respectively.Under strong turbulence,the eigenstate recognition accuracy of S-ConvNeXt is 5.7%,3%and 1.2%higher than that of ResNet50,ShuffleNetV2 and Conv NeXt,and the superposition state recognition accuracy of S-Conv NeXt is 5.7%,4%and 0.9%higher than that of ResNet50,ShuffleNetV2 and ConvNeXt respectively.S-Conv NeXt can effectively improve the accuracy of mode recognition,especially in strong turbulence.
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