Libiq is a modular and extensible library designed for the manipulation, visualization, and classification of I/Q (In-phase and Quadrature) samples.
It is structured into four main classes:
-
Analyzer
Provides tools for manipulating and analyzing time-series I/Q samples.- Supports reading binary/CSV files and extracting real, imaginary, or complex components.
- Includes FFT and PSD methods for frequency-domain analysis.
-
Plotter
Enables real-time visualization of I/Q signals through various plot types:- Scatterplots:
- Plot I vs Q to visualize signal characteristics.
- Plot magnitude or phase over time to capture signal evolution.
- Spectrograms: Compute and visualize time-varying frequency content using FFT. It supports custom window size and overlap settings for tuning resolution:
- Smaller windows capture fine-grained variations.
- Larger windows provide a broader overview of long-term signal behavior.
- Scatterplots:
-
Preprocessor
Handles I/Q data preprocessing for CNN training pipelines.- Converts binary/CSV files into structured datasets.
- Implements energy peak detection to isolate RFI signals and ensure model generalization.
-
Classifier
Contains methods to train and test a lightweight CNN model for RF signal classification. It uses real/imaginary parts, magnitude, and phase as input features.
Libiq has been successfully tested with python 3.9, 3.10, 3.11 and 3.12.
If you use the libiq library to develop your own works, please cite the following paper:
@inproceedings{olimpieri2025libiq,
author = {Olimpieri, Filippo and Giustini, Noemi and Lacava, Andrea and D’Oro, Salvatore and Melodia, Tommaso and Cuomo, Francesca},
title = {{LibIQ: Toward Real-Time Spectrum Classification in O-RAN dApps}},
booktitle = {Proceedings of the IEEE Mediterranean Communication and Computer Networking Conference (MedComNet)},
year = {2025},
address = {Cagliari, Italy},
organization = {IEEE}
}
arxiv url: https://arxiv.org/abs/2505.10537
There are two different ways to install Libiq
The easiest way to install libiq is through PyPI. Simply run:
pip install libiq
It also offers optional dependencies, such as ydata-profiling and scienceplot, which can be installed as follows:
To enable reporting features:
pip install libiq[report]
To enable enhanced plotting styles:
pip install libiq[styles]
Or, to install all optional features at once:
pip install libiq[all]
To verify that the library has been installed correctly, a test script is provided in the docs
directory under the name test_libiq.py
.
You can run it using pytest:
pytest -v test_libiq.py
We provide a bash script that autmatically performs the steps described in Source installation.
To run it you simply need to execute
sudo ./build.sh
Install the basic tools required to build the libraries:
sudo apt install graphviz swig -y
To work properly, Libiq needs FFTW.
The installation steps for this library starts with the download of the sources from the official site of FFTW, in particular we need fftw-3.3.10
mkdir libs
wget -O "libs/fftw-3.3.10.tar.gz" https://fftw.org/fftw-3.3.10.tar.gz
tar -xzf "libs/fftw-3.3.10.tar.gz" -C "libs/"
rm libs/fftw-3.3.10.tar.gz
Then we build and install
cd libs/fftw-3.3.10
./configure --enable-shared --with-pic --enable-threads
make -j$(nproc)
sudo make install
cd ../../
sudo ldconfig
This repository uses hatch
for building the package.
hatch build
pip install dist/libiq-*.tar.gz
Then if you want to install the optional dependencies, do as in Package repository installation