This repository is accompanying the paper "Securing Data in Multimode Fibers by Exploiting Mode-Dependent Light Propagation Effects" (S. Rothe, K.-L. Besser, D. Krause, R. Kuschmierz, N. Koukourakis, E. Jorswieck, J. Czarske. Research, vol. 6: 0065, Jan. 2023. DOI:10.34133/research.0065, arXiv:2203.02064).

The idea is to make all calculations, simulations, and presented results publicly available to the reader and, therefore, reproducible.

The following files are provided in this repository:

• BPSK Secrecy Rate.ipynb: Jupyter notebook that contains an interactive version of the simulations.
• run.sh: Bash script that reproduces the figures presented in the paper.
• statistic.sh: Bash script that reproduces the results which are averaged over multiple measurements.
• svd_precoding.py: Python module that calculates the secrecy rate with SVD precoding.
• no_precoding.py: Python module that calculates the secrecy rate when no precoding at the transmitter is performed.
• data_transmission.py: Python module that shows the measured data transmission of the TU Dresden logo and performs the MC simulation with an additional polar wiretap code.
• waterfilling.py: Python module that solves the optimization problem of optimal power allocation for parallel BSCs.
• show_capacity_statistics.py: Python module that averages the results of multiple MMF measurements and plots them. (Automatically called at the end of statistic.sh.)
• read_matrices.py: Python module that contains functions for reading the channel matrices from the measurement files.
• util.py: Some utility functions like setting up the logging etc.

In the measurements/ directory, one can find the measured MMF channel matrices that where used to obtain the results. All measurements were performed on a 55-mode MMF of 10m length, where an eavesdropper is physically coupled (50:50 coupling). A detailed description can be found in the paper.

• mmf-measurement.mat: Channel matrix measurements of Alice to Bob and Alice to Eve, both with and without precoding at the transmitter
• data-measurement.mat: Measurements of the transmission of the TU Dresden logo

The easiest way is to use services like Binder to run the notebook online. Simply navigate to https://mybinder.org/v2/gh/klb2/mmf-physec/HEAD to run the notebooks in your browser without setting everything up locally.

If you want to run it locally on your machine, Python3 and Jupyter are needed. The present code was developed and tested with the following versions:

• Python 3.10
• Jupyter 1.0
• notebook 6.4
• numpy 1.22
• scipy 1.8
• Pandas 1.4.1
• h5py 3.6
• digcommpy 0.9

Make sure you have Python3 installed on your computer. You can then install the required packages (including Jupyter) by running

pip3 install -r requirements.txt

This will install all the needed packages which are listed in the requirements file.

Finally, you can run the Jupyter notebook with

jupyter notebook 'BPSK Secrecy Rate.ipynb'

You can also recreate the figures from the paper by running

bash run.sh

This research was supported in part by the Deutsche Forschungsgemeinschaft (DFG) under grants JO 801/25-1 and CZ 55/42-1.

This program is licensed under the GPLv3 license. If you in any way use this code for research that results in publications, please cite our original article listed above.

You can use the following BibTeX entry

@article{Rothe2023mmfphysec,
	author = {Rothe, Stefan and Besser, Karl-Ludwig and Krause, David and Kuschmierz, Robert and Koukourakis, Nektarios and Jorswieck, Eduard A. and Czarske, Jürgen W.},
	title = {Securing Data in Multimode Fibres by Exploiting Mode-Dependent Light Propagation Effects},
	journal = {Research},
	year = {2023},
	month = {1},
	volume = {6},
	eid = {0065},
	publisher = {American Association for the Advancement of Science (AAAS)},
	archiveprefix = {arXiv},
	eprint = {2203.02064},
	primaryclass = {physics.app-ph},
	doi = {10.34133/research.0065},
}