Low Complexity Convolutional Neural Networks for Equalization in Optical Fiber Transmission
arXiv:2210.05454 · doi:10.1364/SPPCOM.2021.SpM5C.5
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.
2 pages, 3 figures. Submitted to the OSA Advanced Photonics Congress 2021. Presented in Signal Processing in Photonic Communications (SPPCom) 2021. From the session: Neural Networks Applications for Photonic Systems (SpM5C)