| --- |
| pretty_name: RepresentationLearning ORACLE triplets |
| tags: |
| - wireless |
| - rf-fingerprinting |
| - channel-estimation |
| - cfo-estimation |
| - iq-samples |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # RepresentationLearning dataset |
|
|
| Preprocessed WiFi packets for three wireless tasks, used to train and attack the |
| multi-task representations in |
| [RepresentationLearning](https://github.com/nasimsoltani/RepresentationLearning). |
| Pretrained models and the run registry are in |
| [`Aadharsh/RepresentationLearning-models`](https://huggingface.co/Aadharsh/RepresentationLearning-models). |
|
|
| The packets are derived from the [ORACLE RF fingerprinting dataset](https://genesys-lab.org/oracle) |
| (16 USRP X310 transmitters recorded at 11 distances, 2–62 ft). |
|
|
| ## Files |
|
|
| | File | Size | Contents | |
| |---|---|---| |
| | `OracleDatasetProcessed-arranged.tar.gz` | 3.3 GB | 416,244 `.mat` files (see below) | |
| | `rf_partition_dict_0.5.pkl` | 5.8 MB | train/val/test split and CFO normalisation constants | |
|
|
| ## Layout |
|
|
| ```bash |
| tar xzf OracleDatasetProcessed-arranged.tar.gz |
| ``` |
|
|
| The archive has a doubled top-level directory. The `.mat` files are in |
| `OracleDatasetProcessed-arranged/OracleDatasetProcessed-arranged/`; point |
| `DATA_BASE_PATH` there. |
|
|
| One sample is a **triplet** sharing the suffix `_run1_Radio<r>_<d>ft_<i>.mat`: |
|
|
| | Prefix | Variables | Task | |
| |---|---|---| |
| | `RFfingerprinting` | `Packet` (4000×1 complex), `Radio` (label, `"Radio0"`–`"Radio15"`) | RF fingerprinting (16 classes) | |
| | `CFOEstimation` | `LSTF` (160×1 complex), `CFO` (scalar, Hz) | CFO estimation | |
| | `ChannelEstimation` | `LLTF` (160×1 complex), `EstChannnel` (52×1 complex) | Channel estimation | |
|
|
| `EstChannnel` really is spelled with three n's. The archive also contains 24,525 |
| `CFOEstimation` files without RF/channel partners; no split references them. |
|
|
| ## Split |
|
|
| `rf_partition_dict_0.5.pkl` is a dict: |
|
|
| | Key | Value | |
| |---|---| |
| | `train` / `val` / `test` | lists of `RFfingerprinting_*.mat` filenames: 91,323 / 13,070 / 26,180 | |
| | `mean_cfo`, `std_cfo`, `max_cfo` | CFO statistics of the training split, used to normalise CFO targets | |
|
|
| Filenames are relative to `DATA_BASE_PATH`. The registry's test metrics for runs |
| from July 2025 onward were computed on this split, so use it unchanged when |
| comparing with the registry. |
|
|
| ## Loading |
|
|
| ```bash |
| git clone https://github.com/nasimsoltani/RepresentationLearning.git |
| cd RepresentationLearning && cp .env.example .env # set DATA_BASE_PATH and PKL_FILE_PATH |
| python code/rep_lr/inference.py # evaluate the best released model |
| ``` |
|
|
| Each input is normalised to unit RMS and split into I/Q channels by |
| `code/rep_lr/py_datasets.py`. |
|
|
| ## Citation |
|
|
| The ORACLE authors ask that any publication using their data cite: |
|
|
| ```bibtex |
| @inproceedings{sankhe2019oracle, |
| title={ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks}, |
| author={Sankhe, Kunal and Belgiovine, Mauro and Zhou, Fan and Riyaz, Shamnaz and Ioannidis, Stratis and Chowdhury, Kaushik}, |
| booktitle={IEEE INFOCOM 2019 - IEEE Conference on Computer Communications}, |
| pages={370--378}, |
| year={2019} |
| } |
| ``` |
|
|
