zhuwenxing/claude

End-to-end learning of optical communication systems

Claude

This repository provides helper functions and models for end-to-end learning of optical communication systems.

In particular, this repository provides an implementation for our paper "Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities" [https://arxiv.org/abs/1805.03785] and our manuscript "Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning" [https://arxiv.org/abs/1810.00774].

Content

Example of fiber model

Example of end-to-end learning of geometric constellation shapes with an AWGN channel

Example of end-to-end learning of geometric constellation shapes with a fiber channel model

Example of learning of geometric constellation shapes with no channel info over an AWGN channel [https://arxiv.org/abs/1804.02276]

Acknowledgements

The learning algorithm learns by embedding a fiber channel model within an autoencoder. The implementation of the fiber channel model is copied from a MATLAB implementation by Dar et al. [https://www.osapublishing.org/oe/abstract.cfm?uri=oe-22-12-14199, https://arxiv.org/abs/1310.6137]. Please cite the authors appropriately if you use the here provided Python implementation.

Numpy model [claude/claude/models/NLIN.py]

Tensorflow model [claude/claude/claudeflow/models/NLIN.py]

Installation using Anaconda on Ubuntu

Install Anaconda from https://www.anaconda.com/download/

Clone the git repository into your filesystem

git clone https://github.com/rassibassi/claude

Enter the git repository

cd claude

Create a new conda environment

conda create -n claudeDev python=3.6 pip scipy jupyter matplotlib

Activate the new environment

source activate claudeDev

Install TensorFlow as instructed here: https://www.tensorflow.org/install/install_linux#InstallingAnaconda

Install the local claude pip package

pip install -e claude

This will install claude from the claude folder.

Check if everything is installed

pip list | grep -E 'claude|tensorflow|numpy|scipy|jupyter|matplotlib'

Output:

claude             0.1       /home/path-to-some-folder/claude
jupyter            1.0.0     
jupyter-client     5.2.3     
jupyter-console    5.2.0     
jupyter-core       4.4.0     
matplotlib         2.2.3     
numpy              1.15.1    
scipy              1.1.0     
tensorflow         1.10.1

Start Jupyter with

jupyter notebook

Open the Jupyter notebooks in the example directory. Then you can click on Kernel -> Restart & Run All