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Conferences > OFC > 2023 > Th1F > Th1F.7

Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization Problem of Recurrent Connection

Sasipim Srivallapanondh, Pedro J. Freire, Bernhard Spinnler, Nelson Costa, Antonio Napoli, Sergei K. Turitsyn, and Jaroslaw E. Prilepsky

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Abstract

To circumvent the non-parallelizability of recurrent neural network-based equalizers, we propose knowledge distillation to recast the RNN into a parallelizable feed-forward structure. The latter shows 38% latency decrease, while impacting the Q-factor by only 0.5 dB.

© 2023 The Author(s)

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