CommKit
High-performance digital communications research kit for Python.
CommKit is a Python library for digital communications research that treats hardware as a first-class concern. A single Signal object carries IQ samples, physical metadata, and modulation context - with DSP operations dispatching automatically to NumPy, CuPy, or JAX based on data location.
Why CommKit?
- One object, complete context: Sampling rate, symbol rate, modulation format, and pulse shape travel with the signal through the processing pipeline.
- Backend-transparent DSP:
dispatch()resolves NumPy, CuPy, or SciPy modules at runtime. The same code executes seamlessly on CPU or GPU. - Method chaining: High-level fluent API (
sig.to("gpu").fir_filter(taps).resample(sps_out=2)...) for rapid prototyping. - JAX escape hatch: Zero-copy DLPack export on GPU allows direct application of JAX transforms (gradients,
vmap,scan) without leaving the research loop.
Modules & Features
| Module | Key Capabilities & Features |
|---|---|
commkit.core |
Signal container (IQ samples + metadata), SingleCarrierFrame, Preamble, and symbol/frame factories (PAM, PSK, QAM). |
commkit.backend |
Hardware abstraction layer (dispatch, to_device, to_jax, from_jax), placement management, and backend execution (NumPy, CuPy, JAX). |
commkit.mapping |
Gray-coded constellations, symbol mapping, hard demapping, soft LLR computation (max-log and exact log-sum-exp via JAX JIT), and GMI. |
commkit.filtering |
Pulse shaping (RRC, RC, Gaussian, Smooth-Rectangle), tap generators, matched filtering, Overlap-Save, and polyphase multirate filtering. |
commkit.multirate |
Fractional and integer sample rate conversion (resample, decimate, upsample, decimate_to_symbol_rate). |
commkit.timing |
Preamble generation (Barker, Zadoff-Chu), cross-correlation timing delay estimation, and frame alignment. |
commkit.frequency |
Carrier frequency offset estimation (FOE via M-th power, Mengali-Morelli, Jacobsen) and phase-locked FOE correction. |
commkit.recovery |
Carrier phase recovery (CPR via Viterbi-Viterbi, BPS, DD-PLL) and cycle-slip detection/correction. |
commkit.equalization |
Adaptive equalizers (lms, rls, cma, rde, zf), butterfly MIMO topology support, with Numba JIT and JAX execution backends. |
commkit.impairments |
Channel impairments simulation: AWGN (with SPS correction), PMD (differential group delay, Jones matrix), phase noise, IQ imbalance, and chromatic dispersion. |
commkit.coding |
Channel coding and FEC primitives (BCH, Convolutional, CRC, Galois field arithmetic, Hamming, Interleaving, LDPC, Polar, Rate matching, Reed-Solomon, Turbo codes). |
commkit.metrics |
System performance evaluation: EVM (%, dB), data-aided SNR, and BER estimation. |
commkit.analysis |
Laser phase and linewidth characterization: DSH, homodyne IQ, zero-phase drift detrending, AWGN-free lag-slope linewidth fit, Di Domenico $\beta$-separation line FWHM, and Allan deviation. |
commkit.spectral |
Welch PSD estimation and frequency shifting with bin-quantized mixing. |
commkit.io |
Signal persistence and disk serialization (load_npz, save_npz). |
commkit.plotting |
Visualization tools for constellations, eye diagrams, PSDs, time-domain signals, filter responses, and equalizer convergence. |
commkit.helpers |
General DSP helpers: random bit/symbol generators, array normalization, RMS calculation, and SI prefix formatting. |
Installation & Usage
Requires Python 3.12+ and uv.
Core Installation (CPU)
# Using uv (Recommended)
uv pip install git+https://github.com/lokgar/commkit.git
# Or with standard pip
pip install git+https://github.com/lokgar/commkit.git
GPU Support
To install with CUDA acceleration (includes JAX CUDA 13 and CuPy stacks):
# Using uv
uv pip install "commkit[gpu] @ git+https://github.com/lokgar/commkit.git"
# Or with standard pip
pip install "commkit[gpu] @ git+https://github.com/lokgar/commkit.git"
Development Installation
git clone https://github.com/lokgar/commkit.git
cd commkit
# Sync core environment
uv sync
# Sync environment with all extras (including GPU packages)
uv sync --all-extras
Examples & Notebooks
For complete usage scripts and DSP examples, explore the examples/ directory.
Running Tests
# CPU test suite
uv run pytest --device=cpu
# GPU test suite (requires CuPy + CUDA)
uv run pytest --device=gpu
# Run all test suites
uv run pytest --device=all
License
This project is licensed under the MIT License.
1 maintainer
Metadata
1 maintainer
Release files for commkit 1.0.0
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