With RFix
- Place emitters and a receiver on the RF map.
- Connect signals, interference, and ITU-R or Sionna paths.
- Inspect the IQ and export labels, SigMF, and the source project.
RFix vs Sionna
A complete RF workflow vs differentiable research libraries.
RFix makes Sionna RT usable inside a complete visual workflow with signal design, maps, ITU-R models, interference, IQ analysis, traceable datasets, APIs, and MCP. Sionna alone provides powerful differentiable PHY, system simulation, and ray tracing, but teams must build the surrounding product workflow in code.
RFix advantage: Visual Sionna and ITU-R scenarios that finish as usable, traceable IQ datasets.
Choose Sionna (NVIDIA) mainly for: Differentiable PHY/SYS research and direct radio ray tracing.
Why choose RFix
The easier end-to-end RF workflow.
RFix removes the integration work between scenario design, propagation, IQ analysis, datasets, and automation.
You want Sionna-based propagation inside a visual map, signal, analysis, and dataset product.
You need ITU-R models, interference scenarios, and labeled IQ/SigMF in the same workflow.
You want batch or MCP automation without building and maintaining every surrounding product layer.
Workflow advantage
What RFix includes in one product.
| Capability | RFix | Sionna (NVIDIA) |
|---|---|---|
| Product scope | Integrated product for RF design, scenes, propagation, IQ, datasets, and automation. | Open-source Python modules for PHY, system-level simulation, and radio ray tracing.[1] |
| Visual authoring | Drag-and-drop signal graph and map are the primary scenario interface. | Python and Jupyter notebooks connect modular components into research simulations.[1][2] |
| Maps & terrain | Visual RF placement, motion, terrain, and height-aware editing tied to the graph. | Models 3D scenes and paths, but has no RF project map or dataset workspace.[1] |
| Propagation & research | Combines Sionna RT paths with terrestrial and earth-space ITU-R models. | Differentiable RT, PHY, and SYS with PyTorch, Mitsuba 3, Dr.Jit, and GPUs.[1] |
| IQ import & analysis | Interactive spectrogram and time-domain analysis for measured or generated IQ. | Tensor and array analysis through Python and notebook visualizations.[1] |
| Labels & deliverables | Built-in labels, raw IQ, SigMF pairs, and portable visual projects. | Users build labels, storage, and packaging around framework tensors.[1] |
| RF hardware | Built-in SDR I/O plus paired VSG/analyzer control, waveform playback, measurements, IQ capture, and SCPI. | No built-in VSG, signal-analyzer, or general SCPI instrument workbench.[1] |
| Automation & AI agents | Batch APIs and native MCP tools plan, generate, inspect, and export RF projects. | No native MCP project or RF dataset workflow; automation uses the Python modules.[1] |
| Licensing | Commercial platform with free and licensed capabilities. | Open source and free.[1] |
Concrete workflow
How RFix simplifies: Build a terrain-aware multi-emitter interference dataset.
With Sionna (NVIDIA)
- Code the scene, radio paths, and PHY components.
- Build the multi-emitter generation and labeling pipeline.
- Analyze and package tensors with Python or notebook tooling.
Specialist exception
When Sionna (NVIDIA) is the specialist choice.
Choose Sionna (NVIDIA) primarily when one of these specialist requirements matters more than an integrated scenario-to-IQ workflow:
- You need direct differentiable control of PHY, system-level, or ray-tracing components.
- You want open-source PyTorch-based communications research modules or direct Mitsuba/Dr.Jit RT access.
- You are comfortable building your own authoring, labeling, analysis, and export layers.
The short version
RFix packages Sionna propagation with visual authoring, maps, ITU-R, interference, IQ analysis, datasets, APIs, and MCP. Choose Sionna directly mainly for differentiable research or low-level ray-tracing control.
See it on your own scenario
The fastest way to compare is on your data. We can generate a sample labeled dataset from a scenario like yours so you can judge the fit directly.
Explore RFix
See the workflow in context.
Verification
Official sources.
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