Low Complexity Convolutional Neural Networks for Equalization in Optical Fiber Transmission

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Oct 11, 2022
Mohannad Abu-romoh, Nelson Costa, Antonio Napoli, João Pedro, Yves Jaouën, Mansoor Yousefi
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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)  
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