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Optical Communications Algorithms with Python

Project description

OptiCommPy: Fiber Optic Communications with Python

Simulate optical communications systems with Python. This repository is a Python-based framework to simulate systems, subsystems, and components of fiber optic communication systems, for educational and research purposes.

Binder

Available features

  • Several digital modulations available (M-PAM, square M-QAM, M-PSK, OOK) to simulate IM-DD and coherent optical systems.
  • Numerical models to simulate optical transmitters, optical amplification, nonlinear propagation over optical fibers, and optical receivers.
  • CPU and GPU-based implementations of the split-step Fourier Method to simulate polarization multiplexed WDM transmission.
  • Standard digital signal processing (DSP) blocks employed in coherent optical receivers, such as:
    • Signal resampling.
    • Matched filtering.
    • Electronic chromatic dispersion compensation (EDC).
    • Several NxN MIMO adaptive equalization algorithms.
    • Carrier phase recovery algorithms.
  • For most of the cases, Numba is used to speed up the core DSP functions.
  • Evaluate transmission performance with metrics such as:
    • Bit-error-rate (BER).
    • Symbol-error-rate (SER).
    • Error vector magnitude (EVM).
    • Mutual information (MI).
    • Generalized mutual information (GMI).
    • Normalized generalized mutual information (NGMI).
  • Visualization of the spectrum of electrical/optical signals, signal constellations, and eyediagrams.

How can I contribute?

If you want to contribute to this project, implement the feature you want and send me a pull request. If you want to suggest new features or discuss anything related to OptiCommPy, please get in touch with me (edsonporto88@gmail.com).

Requirements/Dependencies

  • python>=3.2
  • numpy>=1.9.2
  • scipy>=0.15.0
  • matplotlib>=1.4.3
  • scikit-commpy>=0.7.0
  • numba>=0.54.1
  • tqdm>=4.64.1
  • simple-pid>=1.0.1
  • mpl-scatter-density>=0.7.0

Installation

Using pip:

pip install OptiCommPy

Cloning the repository from GitHub:

$ git clone https://github.com/edsonportosilva/OptiCommPy.git
$ cd OptiCommPy
$ python setup.py install

or

$ git clone https://github.com/edsonportosilva/OptiCommPy.git
$ cd OptiCommPy
$ pip install .

Citing this repository

Edson Porto da Silva, Adolfo Herbster, & Joaquin Matres. (2022). edsonportosilva/OptiCommPy: v0.2.0-alpha (v0.2.0-alpha). https://doi.org/10.5281/zenodo.7425071

DOI

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OptiCommPy-0.6.0.tar.gz (49.6 kB view hashes)

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