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.

Sionna是一款基于TensorFlow的GPU加速开源库，可用于快速原型设计复杂的通信系统构架，支持神经网络集成，并使用测试过的最新算法进行基准测试和端到端性能评估，是6G等下一代通信系统研究的有价值的工具。

Sionna：下一代物理层研究的开源库