Have you ever had a great idea, but the time to re-implement existing schemes did prevent you from having a closer look? With Sionna, you can skip the time consuming ramp-up and immediately start realizing your own research ideas.
Although many machine learning concepts often sound simple at first sight, their detailed implementation can be time consuming and sometimes tricky. Sionna aims at keeping this barrier-to-entry for machine learning for communications research as low as possible. The following list of interactive examples can be directly executed, modified, and re-used as blueprint for your own research.
Furthermore, supporting reproducible research is one of our key intentions. We hope that many researchers will publish their latest results as (annotated) Jupyter notebooks in this unified framework.
- 5G Channel Coding and Rate-Matching: Polar vs. LDPC Codes
- 5G NR PUSCH Tutorial
- Bit-Interleaved Coded Modulation (BICM)
- MIMO OFDM Transmissions over the CDL Channel Model
- Neural Receiver for OFDM SIMO Systems
- Realistic Multiuser MIMO OFDM Simulations
- OFDM MIMO Channel Estimation and Detection
- Introduction to Iterative Detection and Decoding
- End-to-end Learning with Autoencoders
- Weighted Belief Propagation Decoding
- Channel Models from Datasets
- Using the DeepMIMO Dataset with Sionna