cu3GPPChan Python Bindings

Python interface to the GPU-accelerated cu3gppchan C++/CUDA library via nanobind.

Prerequisites

Component	Version
Python	3.10+
CUDA Toolkit	12.x+
GPU	SM 8.0+ (Ampere / Hopper)
numpy	any
h5py	any
pyyaml	any
cupy (optional)	`cupy-cuda13x` — required for `StatisticalChannel` and `FadingChannel`

The wheel build invokes the repo CMake project and packages both _cu3gppchan*.so and libchanModels.so into the wheel. The target machine must still provide the CUDA driver/runtime and system libraries such as HDF5.

Build a Wheel

# From the repository root:
bash scripts/build_wheel.sh --clean

# Install the generated wheel
python3 -m pip install dist/cu3gppchan-*.whl

# Verify import and basic config construction
python3 scripts/use_python_wheel.py

Set CUDA architectures with:

CU3GPPCHAN_CUDA_ARCHS="80;90" bash scripts/build_wheel.sh --clean

For editable development:

bash scripts/build.sh --python
python3 -m pip install -e python/

Verify:

import cu3gppchan
print(cu3gppchan.__version__)  # 0.1.1

Package Structure

python/
  pyproject.toml
  src/cu3gppchan/
    __init__.py              Public API re-exports
    _cu3gppchan*.so          nanobind C++ extension (built by CMake)
    libchanModels.so         bundled runtime library used by the extension
    statistical_channel.py   StatisticalChannel — system-level SLS wrapper
    fading_channel.py        FadingChannel — link-level TDL/CDL wrapper
    channel_config.py        TdlChannelConfig / CdlChannelConfig
    channel_api_ref.py       3GPP TR 38.901 reference data
    cuda_utils.py            CUDA stream and array helpers

API Overview

Low-Level Bindings (no CuPy needed)

These are direct nanobind wrappers of C++ classes. Use when you manage GPU memory yourself or only need configuration objects.

Class	Description
`SimConfig`	Simulation parameters (frequency, bandwidth, run mode)
`SystemLevelConfig`	Scenario, topology (sites, sectors, UTs)
`LinkLevelConfig`	Fading type, delay profile, mobility
`ExternalConfig`	External cell/UT/antenna configuration
`TdlConfig` / `TdlChan`	TDL channel config and engine
`CdlConfig` / `CdlChan`	CDL channel config and engine
`StatisChanModel`	System-level stochastic channel engine
`GauNoiseAdder`	AWGN noise on GPU
`OfdmModulate` / `OfdmDeModulate`	OFDM mod/demod
`Scenario`	Enum: `UMa`, `UMi`, `RMa`, etc.

High-Level Wrappers (require CuPy)

These provide a Pythonic interface with CuPy array I/O and automatic GPU memory management.

`StatisticalChannel` — System-Level Channel

from cu3gppchan import (
    StatisticalChannel, SimConfig, SystemLevelConfig,
    LinkLevelConfig, ExternalConfig, Scenario,
)

sim_cfg = SimConfig(center_freq_hz=3.5e9, bandwidth_hz=100e6, run_mode=1)
sys_cfg = SystemLevelConfig(scenario=Scenario.UMa, n_site=1, n_ut=10)
link_cfg = LinkLevelConfig(fast_fading_type=2)  # CDL
ext_cfg = ExternalConfig()

chan = StatisticalChannel(sim_cfg, sys_cfg, link_cfg, ext_cfg)

# Run one TTI
chan.run(ref_time=0.0)

`FadingChannel` — Link-Level TDL / CDL

from cu3gppchan import FadingChannel, TdlChannelConfig

config = TdlChannelConfig(
    n_cell=1, n_ue=1,
    n_bs_ant=4, n_ue_ant=4,
    delay_profile='A',
    delay_spread_ns=30,
    max_doppler_hz=5,
    sc_spacing_hz=30e3,
)

chan = FadingChannel(config)
rx_signal = chan.run(tx_signal, ref_time=0.0, snr_db=20.0)

Configuration Classes

Class	Description
`TdlChannelConfig`	TDL channel parameters (profiles A–E, delay spread, Doppler)
`CdlChannelConfig`	CDL channel parameters (antenna arrays, spatial correlation)
`CellParam`	Per-cell parameters (position, antenna panel)
`UtParamCfg`	Per-UT parameters (position, velocity, type)
`AntPanelConfig`	Antenna panel geometry `[M_g, N_g, M, N, P]` per TR 38.901

Enums

Enum	Values
`Scenario`	`UMa`, `UMi`, `RMa`, `InH`, `InF`
`SensingTargetType`	ISAC target types
`UeType`	UE mobility types

Running Tests

# Static analysis (flake8 / pylint / mypy)
bash tests/run_static_tests.sh

# Python unit tests
bash tests/run_unit_tests.sh --python_only

Dependencies

Required (installed automatically by pip install):

numpy
h5py
pyyaml

Optional:

cupy-cuda13x — for StatisticalChannel, FadingChannel, and GPU array wrappers

License

Apache-2.0. See file headers for details.

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0.1.4

Aug 4, 2026 3 files

0.1.3

Jul 20, 2026 4 files

0.1.2

Jul 19, 2026 6 files

This release

0.1.1 This release

Jul 18, 2026 7 files

0.1.0

Jun 16, 2026 5 files

cu3gppchan 0.1.1

cu3GPPChan Python Bindings

Prerequisites

Build a Wheel

Package Structure

API Overview

Low-Level Bindings (no CuPy needed)

High-Level Wrappers (require CuPy)

StatisticalChannel — System-Level Channel

FadingChannel — Link-Level TDL / CDL

Configuration Classes

Enums

Running Tests

Dependencies

License

Key dates

1 maintainer

License

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`StatisticalChannel` — System-Level Channel

`FadingChannel` — Link-Level TDL / CDL