  Sionna is a GPU-accelerated open-source library for link-level simulations
based on TensorFlow. It enables the rapid prototyping of complex communication
system architectures and provides native support for the integration of neural
networks. Sionna implements a wide breadth of carefully tested state-of-the-art
algorithms that can be used for benchmarking and end-to-end performance
evaluation. This allows researchers to focus on their research, making it more
impactful and reproducible, while saving time implementing components outside
their area of expertise. This white paper provides a brief introduction to
Sionna, explains its design principles and features, as well as future
extensions, such as integrated ray tracing and custom CUDA kernels. We believe
that Sionna is a valuable tool for research on next-generation communication
systems, such as 6G, and we welcome contributions from our community.
