initial commit

.github/workflows/python-package.yml

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+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
+name: CI
+
+on:
+ push:
+ branches: [ master ]
+ pull_request:
+ branches: [ master ]
+
+jobs:
+ build:
+
+ runs-on: ubuntu-latest
+ strategy:
+ fail-fast: false
+ matrix:
+ python-version: ["3.8"]
+
+ steps:
+ - uses: actions/checkout@v3
+ - name: Set up Python ${{ matrix.python-version }}
+ uses: actions/setup-python@v3
+ with:
+ python-version: ${{ matrix.python-version }}
+ - name: Install dependencies
+ run: |
+ python -m pip install --upgrade pip
+ python -m pip install flake8 pytest
+ if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+ pip install -e .
+ - name: Lint with flake8
+ run: |
+ # stop the build if there are Python syntax errors or undefined names
+ flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+ # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+ flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+ - name: Test with pytest
+ run: |
+ pytest

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

.pre-commit-config.yaml

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+repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+ rev: v2.3.0
+ hooks:
+ - id: check-yaml
+ - id: end-of-file-fixer
+ - id: trailing-whitespace
+- repo: https://github.com/psf/black
+ rev: 22.10.0
+ hooks:
+ - id: black

README.md

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+<div align='center'>
+<p align='center'>
+ <img width='50%' src='./.assets/CeBed_back.png' />
+</p>
+
+
+![Continuous Integration](https://github.com/SAIC-MONTREAL/CeBed/actions/workflows/python-package.yml/badge.svg)
+[![License: CC BY-NC 4.0](https://img.shields.io/badge/License-CC_BY--NC_4.0-blue.svg)](https://creativecommons.org/licenses/by-nc/4.0/)
+[![codestyle](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+</div>
+
+Channel estimation test bed (CeBed) is a suite of implementations and benchmarks for OFDM channel estimation in Tensorflow.
+
+The goal of CeBed is to unify and facilitate the replication, refinement and design of new deep channel estimators. CeBed can also be used as a baseline to create and build new projects and compare with existing algorithms in the litterature. It is simple to add a new dataset or a model to our package and we welcome the community to update or add exisiting algorithms or datasets.
+
+For now, CeBed provides a simple interface to train and evaluate various deep channel estimation models.
+
+# Setup
+
+<details open>
+
+Clone repo and install the requirements in a [**Python>=3.8.0**](https://www.python.org/) environment.
+```bash
+git clone https://github.com/SAIC-MONTREAL/CeBed
+cd CeBed
+pip install -e .
+```
+</details>
+
+<!--# Setup
+CeBed can be installed as follows
+-->
+
+# Using CeBed
+## Datasets
+### Sionna dataset
+<details>
+For now, CeBed uses the link-level simulator [Sionna](https://nvlabs.github.io/sionna/) for data generation. CeBed provides an interface to generate datasets using different channel models, system parameters, pilot patterns, etc.
+
+Here is an example to generate a `SISO` dataset using one SNR level (by default = 0 dB) :
+```bash
+python scripts/generate_datasets_from_sionna.py --size 10000 --num_rx_antennas 1 --path_loss
+```
+The generated dataset contains:
+- `x`: Transmitted symbols, a complex tensor with shape `[batch_size, num_tx, num_tx_ant, num_ofdm_symbols, num_subcarriers]`
+- `h`: The channel impulse response, a complex tensor with shape `[batch size, num_rx, num_rx_ant, num_tx, num_tx_ant, num_ofdm_symbols, num_subcarriers]`
+- `y`: The received symbols, a complex tensor with shape `[batch size, num_rx, num_rx_ant, num_ofdm_symbols, num_subcarriers]`
+
+Here is another example on how to generate a multi-domain dataset where each SNR level is a different domain:
+```bash
+python scripts/generate_datasets_from_sionna.py --size 10000 --scenario umi --num_rx_antennas 1 --path_loss --num_domains 5 start_ds 0 end_ds 25
+```
+</details>
+
+### Custom dataset
+<details>
+It is easy to add a new dataset to CeBed. The dataset can be generated offline using any link-level simulator like MATLAB.
+
+Please check the tutorial in [notebooks/cusotm_dataset.ipynb](notebooks/custom_dataset.ipynb), detailing how to use CeBed with your dataset.
+</details>
+
+## Training
+
+<details>
+<summary>Single model training</summary>
+
+The command below will train and evaluate a single model
+```bash
+python scripts/train.py --experiment_name EXPERIMENT_NAME --seed SEED --data_dir DATADIR --epochs 100 --dataset_name SionnaOfflineMD --model_name ReEsNet --input_type low
+```
+</details>
+
+<details>
+<summary>Model hyperparameters</summary>
+
+The model hyperprameters are defined in `yaml` files under [hyperparams](./hyperparams).
+Make sure that the `EXPERIMENT_NAME` exists in the yaml files of the model(s) you would like to train.
+Here is an example configuration of the [ReEsNet model](./hyperparams/ReEsNet.yaml):
+```yaml
+MyExperimentName:
+ default:
+ hidden_size: 16
+ input_type: low
+ kernel_size: 3
+ lr: 0.001
+ n_blocks: 4
+ upsamling_mode: deconv
+```
+</details>
+
+<details>
+<summary>Benchmarking all models</summary>
+
+To reproduce the benchamrking results from our paper:
+```python
+python scripts/benchmark.py --seed SEED --data_dir DATADIR --epochs 100 --experiment_name EXPERIMENT_NAME --gpus GPU_IDS
+```
+
+**Note**: The model inputs and outputs are expects to have the following shape `[batch_size, num_ofdm_symbols, num_ofdm_subcarriers, num_channels]` where `num_channels = num_rx_ant*num_tx*2`.
+
+</details>
+
+## Evaluation
+<details>
+**Evaluate a trained model**
+
+To evaluate a model trained with CeBed,
+```
+python scripts/evaluate.py PATH_TO_MODEL
+```
+
+**Evaluate model and baselines**
+
+You can provide a list of baselines to compare the model to :
+```
+python scripts/evaluate.py PATH_TO_MODEL LS LMMSE ALMMSE
+```
+</details>
+
+
+# Citation
+If you use our code, please cite our work.
+```bibtex
+@article{cebed,
+ author = {Amal Feriani and Di Wu and Steve Liu and Greg Dudek},
+ title = {CeBed: A Benchmark for Deep Data-Driven OFDM Channel Estimation},
+ url = {https://github.com/SAIC-MONTREAL/cebed.git}
+ yeart = {2023}
+}
+```
+
+# License
+
+The code is licensed under the [Creative Commons Attribution 4.0 License (CC BY)](https://creativecommons.org/licenses/by/4.0/).

cebed/__init__.py

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+__version__ = "1.0"