RF Chain Modeling

RF Signal Simulation and Analysis Framework

RF_chain_modeling is a Python framework designed to model, simulate, and analyze Radio Frequency (RF) chains. It allows you to cascade various RF components—such as amplifiers, filters, cables, and antennas—to predict system performance metrics like Gain, Noise Figure (NF), and non-linearities (OP1dB, IP3, IP2).

Key Features

• Component Modeling: built-in models for Attenuators, Amplifiers, Cables, Filters (HighPass, BandPass, LowPass), and Antennas.
• Data-Driven Components: Import component characteristics from CSV/TSV data files (e.g., S-parameters or measured gain/NF).
• Signal Processing: Simulation of time-domain and frequency-domain signals with thermal noise injection.
• Performance Assessment:
  • Gain & Phase: Frequency response analysis.
  • Noise Figure (NF): Cascaded noise analysis.
  • Non-Linearities: Automatic assessment of 1dB Compression Point (P1dB) and Intercept Points (IIP3/OIP3, IIP2/OIP2).

📦 Installation

1. Clone the repository:

   git clone https://github.com/dunaar/RF_chain_modeling.git
   cd RF_chain_modeling

2. Install dependencies: The project relies on standard scientific Python libraries.

   pip install -r requirements.txt

   Required libraries: numpy, scipy, matplotlib, tqdm

📖 Usage Examples

1. Modeling a Full RF Chain

The script rf_chains/rf_chain_example.py demonstrates how to create a complete transmission chain combining a signal generator, an antenna, filters, and amplifiers.

How to run:

python -m RF_chain_modeling.rf_chains.rf_chain_example

What it does:

• Signal Generation: Creates a broad-band signal (40 GHz bandwidth) with thermal noise and three specific tones (at 3, 11, and 17 GHz).
• Chain Definition:
  1. Antenna: Defines frequency-dependent gain.
  2. High-Pass Filter: Cutoff at 6 GHz.
  3. LNA (Low Noise Amplifier): Gain 16 dB, NF 3 dB.
  4. Attenuator: 5 dB attenuation.
  5. Power Amplifier: Gain 20 dB, OIP3 40 dBm.
  6. RF Cable: 10m length with frequency-dependent loss.
  7. Band-Pass Filter: 9-12 GHz passband.
• Simulation: Processes the signal through the chain and plots the Time Domain and Frequency Spectrum before and after processing.
• Assessment: Automatically characterizes the Gain, Noise Figure, and Intercept points (IP2, IP3) of the entire chain and individual components.

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2. Modeling a Specific Component from Data

The script rf_components/zvq_183_s_plus.py shows how to model a specific commercial component (Mini-Circuits ZVQ-183+ amplifier) using measured data stored in a TSV file.

How to run:

python -m RF_chain_modeling.rf_components.zvq_183_s_plus

What it does:

• Data Import: Reads zvq_183_s_plus.tsv using the CSVDataTable utility to parse Frequency, Gain, Phase, NF, and OIP3 data.
• Component Creation: Instantiates an RF_Modelised_Component using the real-world data points.
• Characterization:
  • Interpolates performance metrics across the frequency band (10 MHz - 20 GHz).
  • Calculates and plots Gain, Phase, and Noise Figure vs. Frequency.
  • Assesses linearity (P1dB, IP3) at specific test frequencies.

📂 Project Structure

• rf_utils/: Core utilities for signal processing (Signals class), component base classes, and CSV handling.
• rf_components/: Definitions for specific or generic RF components.
• rf_chains/: Scripts defining and simulating complete RF chains.
• rf_subchains/: Reusable sub-blocks of RF components.

📝 License

This project is licensed under the MIT License. See the LICENSE file for details.

Author: Pessel Arnaud Version: 0.1 (2026-01-03)

Citing

If you use this software in your research, please cite it using the following DOI:

Pessel, A. (2026). RF_chain_modeling (v0.1.0-beta.1). Zenodo. https://doi.org/10.5281/zenodo.18145792