Spiking Neural Network Equalization for IM/DD Optical Communication

TL;DR

This paper introduces a spiking neural network equalizer for IM/DD optical links that matches the performance of artificial neural networks and surpasses linear equalization, optimized for neuromorphic hardware.

Contribution

The paper presents a novel SNN equalizer model tailored for IM/DD links, demonstrating comparable performance to ANNs and improved results over linear methods.

Findings

SNN equalizer achieves same BER as ANN-based equalizer.

Outperforms traditional linear equalization.

Suitable for implementation on neuromorphic hardware.

Abstract

A spiking neural network (SNN) equalizer model suitable for electronic neuromorphic hardware is designed for an IM/DD link. The SNN achieves the same bit-error-rate as an artificial neural network, outperforming linear equalization.