https://github.com/nvlabs/sionna
Sionna: An Open-Source Library for Research on Communication Systems
https://github.com/nvlabs/sionna
5g 6g communications deep-learning differentiable-simulation gpu-acceleration link-level-simulation machine-learning open-source raytracing reproducible-research system-level-simulation
Last synced: 3 days ago
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Sionna: An Open-Source Library for Research on Communication Systems
- Host: GitHub
- URL: https://github.com/nvlabs/sionna
- Owner: NVlabs
- License: other
- Created: 2022-02-15T19:55:30.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2025-12-19T17:16:25.000Z (28 days ago)
- Last Synced: 2025-12-22T07:16:47.666Z (26 days ago)
- Topics: 5g, 6g, communications, deep-learning, differentiable-simulation, gpu-acceleration, link-level-simulation, machine-learning, open-source, raytracing, reproducible-research, system-level-simulation
- Language: Jupyter Notebook
- Homepage: https://nvlabs.github.io/sionna/
- Size: 287 MB
- Stars: 1,267
- Watchers: 39
- Forks: 355
- Open Issues: 31
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
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README
# Sionna: An Open-Source Library for Research on Communication Systems
Sionna™ is an open-source Python-based library for research on
communication systems.
The official documentation can be found
[here](https://nvlabs.github.io/sionna/).
It is composed of the following packages:
- [Sionna RT](https://nvlabs.github.io/sionna/rt/index.html) -
A lightning-fast stand-alone ray tracer for radio propagation modeling
- [Sionna PHY](https://nvlabs.github.io/sionna/phy/index.html) -
A link-level simulator for wireless and optical communication systems
- [Sionna SYS](https://nvlabs.github.io/sionna/sys/index.html) -
A system-level simulator based on physical-layer abstraction
# Installation
Sionna PHY and Sionna SYS require [Python 3.10-3.12](https://www.python.org/) and [TensorFlow 2.14-2.19](https://www.tensorflow.org/install). We recommend Ubuntu 24.04. Earlier versions of TensorFlow may still work but are not recommended. We refer to the [TensorFlow GPU support tutorial](https://www.tensorflow.org/install/gpu) for GPU support and the required driver setup.
Sionna RT has the same requirements as [Mitsuba
3](https://github.com/mitsuba-renderer/mitsuba3) and we refer to its
[installation guide](https://mitsuba.readthedocs.io/en/stable/) for further
information. To run Sionna RT on CPU, [LLVM](https://llvm.org) is required by
[Dr.Jit](https://drjit.readthedocs.io/en/stable/). Please check the
[installation instructions for the LLVM
backend](https://drjit.readthedocs.io/en/latest/what.html#backends). The source
code of Sionna RT is located in a separate [GitHub repository](https://github.com/NVlabs/sionna-rt).
If you want to run the tutorial notebooks on your machine, you also need
[JupyterLab](https://jupyter.org/). You can alternatively test them on [Google
Colab](https://colab.research.google.com/). Although not necessary, we recommend
running Sionna in a [Docker container](https://www.docker.com) and/or [Python virtual
enviroment](https://docs.python.org/3/library/venv.html).
## Installation via pip
The recommended way to install Sionna is via pip:
```
pip install sionna
```
If you want to install only Sionna RT, run:
```
pip install sionna-rt
```
You can install Sionna without the RT package via
```
pip install sionna-no-rt
```
## Installation from source
1. Clone the repository with all submodules:
```
git clone --recursive https://github.com/NVlabs/sionna
```
If you have already cloned the repository but forgot to set the `--recursive`
flag, you can correct this via:
```
git submodule update --init --recursive --remote
```
2. Install Sionna (including Sionna RT) by running the following command from within the repository's
root folder:
```
pip install ext/sionna-rt/ .
pip install .
```
## Testing
First, you need to install the test requirements by executing the
following command from the repository's root directory:
```
pip install '.[test]'
```
The unit tests can then be executed by running ``pytest`` from within the
``test`` folder.
## Building the Documentation
Install the requirements for building the documentation by running the following
command from the repository's root directory:
```
pip install '.[doc]'
```
You might need to install [pandoc](https://pandoc.org) manually.
You can then build the documentation by executing ``make html`` from within the ``doc`` folder.
The documentation can then be served by any web server, e.g.,
```
python -m http.server --dir build/html
```
## For Developers
Development requirements can be installed by executing from the repository's root directory:
```
pip install '.[dev]'
```
Linting of the code can be achieved by running ```pylint src/``` from the repository's root directory.
## License and Citation
Sionna is Apache-2.0 licensed, as found in the [LICENSE](https://github.com/nvlabs/sionna/blob/main/LICENSE) file.
If you use this software, please cite it as:
```bibtex
@software{sionna,
title = {Sionna},
author = {Hoydis, Jakob and Cammerer, Sebastian and {Ait Aoudia}, Fayçal and Nimier-David, Merlin and Maggi, Lorenzo and Marcus, Guillermo and Vem, Avinash and Keller, Alexander},
note = {https://nvlabs.github.io/sionna/},
year = {2022},
version = {1.2.1}
}
```