A New Tandem Learning Rule for Efficient Training of Spiking Neural Network Equalizers for IM/DD Optical Transmission
Conference: ECOC 2024 - 50th European Conference on Optical Communication
09/22/2024 - 09/26/2024 at Frankfurt, Germany
Proceedings: ITG-Fb. 317: ECOC 2024
Pages: 4Language: englishTyp: PDF
Authors:
Li, Shuangxu; Boecherer, Georg; Calabro, Stefano; Schaedler, Maximilian; Kong, Tianyuan
Abstract:
A spiking neural network (SNN) equalizer for IM/DD optical transmission is trained using tandem learning, offloading the training to an artificial neural network (ANN). Optimal performance is achieved, outperforming a linear equalizer by 1 dB. The proposed learning rule is suitable for neuromorphic hardware.