# Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications

arXiv: https://arxiv.org/abs/2402.15288 · HTML: https://mlsanity.com/paper/2402.15288/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 8 references that are in the map.
- First posted on arXiv 23 Feb 2024.

## Builds on (most cited first, 3 of 3)

- [Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems](https://mlsanity.com/paper/2206.12180/) (2022)
- [Unsupervised ANN-Based Equalizer and Its Trainable FPGA Implementation](https://mlsanity.com/paper/2304.06987/) (2023)
- [Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks](https://mlsanity.com/paper/2401.09579/) (2024)

## Abstract (arXiv)

In this work, we present a high-throughput field programmable gate array (FPGA) demonstrator of an artificial neural network (ANN)-based equalizer. The equalization is performed and illustrated in real-time for a 30 GBd, two-level pulse amplitude modulation (PAM2) optical communication system.