# AutoencoderFiber

**Repository Path**: zhoub86/AutoencoderFiber

## Basic Information

- **Project Name**: AutoencoderFiber
- **Description**: This shows how to use Autoencoders for learning constellations and receivers in fiber optical communications
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2021-03-18
- **Last Updated**: 2021-05-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Auto-encoder for a memoryless fiber-optical channel

This script uses an auto-encoder (AE) for end-to-end learning of a non-linear memoryless fiber channel. The determines a good constellation and a good receiver. The achievable information rate is also computed. 

This code was is based on the paper

Shen Li, Christian Häger, Nil Garcia, and Henk Wymeersch, "Achievable Information Rates for Nonlinear Fiber Communication via End-to-end Autoencoder Learning," in *Proc. European Conference on Optical Communication* (2018) [arXiv:1804.07675](https://arxiv.org/pdf/1804.07675.pdf).