# Nonlinear Interference Mitigation via Deep Neural Networks

arXiv: https://arxiv.org/abs/1710.06234 · HTML: https://mlsanity.com/paper/1710.06234/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Oct 2017.

## Built on by (most cited first, 13 of 13)

- [DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator Splitting](https://mlsanity.com/paper/2212.05571/) (2022)
- [Interference Suppression Using Deep Learning: Current Approaches and Open Challenges](https://mlsanity.com/paper/2112.08988/) (2021)
- [Reducing Computational Complexity of Neural Networks in Optical Channel Equalization: From Concepts to Implementation](https://mlsanity.com/paper/2208.12866/) (2022)
- [Performance and Complexity Analysis of bi-directional Recurrent Neural Network Models vs. Volterra Nonlinear Equalizers in Digital Coherent Systems](https://mlsanity.com/paper/2103.03832/) (2021)
- [Hybrid-Layers Neural Network Architectures for Modeling the Self-Interference in Full-Duplex Systems](https://mlsanity.com/paper/2110.09997/) (2021)
- [End-to-End Learning of Joint Geometric and Probabilistic Constellation Shaping](https://mlsanity.com/paper/2112.05050/) (2021)
- [FPGA Implementation of Multi-Layer Machine Learning Equalizer with On-Chip Training](https://mlsanity.com/paper/2212.03515/) (2022)
- [Learned Digital Back-Propagation for Dual-Polarization Dispersion Managed Systems](https://mlsanity.com/paper/2205.11376/) (2022)
- [Implementing Neural Network-Based Equalizers in a Coherent Optical Transmission System Using Field-Programmable Gate Arrays](https://mlsanity.com/paper/2212.04703/) (2022)
- [Neural Network Architectures for Optical Channel Nonlinear Compensation in Digital Subcarrier Multiplexing Systems](https://mlsanity.com/paper/2304.06836/) (2023)
- [Application of Transformers for Nonlinear Channel Compensation in Optical Systems](https://mlsanity.com/paper/2304.13119/) (2023)
- [Multi-Task Learning to Enhance Generalizability of Neural Network Equalizers in Coherent Optical Systems](https://mlsanity.com/paper/2307.05374/) (2023)
- [Equalization in Dispersion-Managed Systems Using Learned Digital Back-Propagation](https://mlsanity.com/paper/2307.06821/) (2023)

## Abstract (arXiv)

A neural-network-based approach is presented to efficiently implement digital backpropagation (DBP). For a 32x100 km fiber-optic link, the resulting "learned" DBP significantly reduces the complexity compared to conventional DBP implementations.