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Sionna RT is the stand-alone ray tracing package of theSionna™ Library for Researchon Communication Systems.It is built on top ofMitsuba 3 and is interoperable withTensorFlow,PyTorch, andJAX.

The official documentation can be found on theSionnawebsite.

The recommended way to install Sionna RT is via pip:

pip install sionna-rt

Sionna RT has the same requirements as Mitsuba 3 and we refer to itsinstallation guide for further information.

To run Sionna RT on CPU,LLVM is required by Dr.Jit.Please check theinstallation instructions for the LLVM backend.

After to cloning the repository, you can installsionna-rt by running the following command from within the repository's root directory:

pip install .

First, you need to install the test requirements by executing thefollowing command from the repository's root directory:

pip install '.[test]'

The unit tests can then be executed by runningpytest from within thetest folder.

Install the requirements for building the documentation by running the followingcommand from the repository's root directory:

pip install '.[doc]'

You might need to installpandoc manually.

You can then build the documentation by executingmake html from within thedoc folder.

The documentation can then be served by any web server, e.g.,

python -m http.server --dir build/html

The documentation of Sionna RT includesdeveloper guidesexplaining how to extend it with custom antenna patterns, radio materials, etc.

Development requirements can be installed by executing from the repository's root directory:

pip install '.[dev]'

Linting of the code can be achieved by runningpylint src/ from therepository's root directory.

Sionna RT is Apache-2.0 licensed, as found in theLICENSE file.

If you use this software, please cite it as:

@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}}