Joint baud-rate and modulation format identification based on asynchronous delay-tap plots analyzer by using convolutional neural network

Abstract In this paper, a joint baud-rate and modulation format identification (BR-MFI) is proposed based on asynchronous delay tap picture (ADTP) analyzer by using convolutional neural network (CNN). Considering 8 types of signals under different channel conditions of OSNR, CD and DGD, the proposed BR-MFI can achieve 100% accuracy after 6 training epochs, and just 2 epochs for MFI. Here, two test number of samples are about 15% of total samples. This paper also investigates the influence of CNN structure on the identification accuracy. The results show that CNN has better performance for image processing than back-propagation Artificial Neural Network (BP-ANN).

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