Low Complexity Convolutional Neural Networks for Equalization in Optical Fiber Transmission
Abstract
A convolutional neural network is proposed to mitigate fiber transmission effects, achieving a five-fold reduction in trainable parameters compared to alternative equalizers, and 3.5 dB improvement in MSE compared to DBP with comparable complexity.
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