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Spiking neural network equalization on neuromorphic hardware for IM/DD optical communication

A spiking neural network (SNN) non-linear equalizer model is implemented on the mixed-signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link. The BER 2e-3 is achieved with a hardware penalty less than 1 dB, outperforming numeric linear equalization.

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Bibliographic Details
Main Authors: Arnold, Elias (Author) , Böcherer, Georg (Author) , Müller, Eric (Author) , Spilger, Philipp (Author) , Schemmel, Johannes (Author) , Calabrò, Stefano (Author) , Kuschnerov, Maxim (Author)
Format: Article (Journal) Chapter/Article
Language:English
Published: 2022-05-11
In: Arxiv
Year: 2022, Pages: 1-6
DOI:10.48550/arXiv.2206.00401
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.48550/arXiv.2206.00401
Verlag, lizenzpflichtig, Volltext: http://arxiv.org/abs/2206.00401
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Author Notes:Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
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Summary:A spiking neural network (SNN) non-linear equalizer model is implemented on the mixed-signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link. The BER 2e-3 is achieved with a hardware penalty less than 1 dB, outperforming numeric linear equalization.
Item Description:Version 1 vom 2022-05-11
Gesehen am 18.10.2022
Physical Description:Online Resource
DOI:10.48550/arXiv.2206.00401

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