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This dataset contains a comprehensive collection of 2D amplitude-phase histograms derived from raw IEEE 802.11 (Wi-Fi) IQ signal captures. It is intended to support research in Automatic Modulation Classification (AMC) under realistic and challenging indoor wireless propagation environments.
The dataset is particularly useful for:
- modulation recognition and classification
- machine learning and deep learning for RF sensing
- channel robustness studies
- SNR-aware signal analysis
- indoor Wi-Fi signal characterization
There are 4 distinct datasets: (1) a synthetic dataset incorporating multipath fading and noise under perfect synchronization, (2) a synthetic dataset including fading, noise, and synchronization impairments, (3) a conducted hardware dataset acquired through cable-based measurements, and (4) an OTA dataset.
Dataset Structure
The dataset follows a hierarchical directory structure that enables easy filtering by:
- channel model / physical scenario
- SNR level (dB)
Path Format
[Channel_Model]/[SNR_dB]/[Filename].mat
File Naming Convention
Each file name encodes important metadata about the captured signal.
Filename Pattern
H_{Format}_{Channel}_{Modulation}_{SNR}_{SampleID}.mat
Component Breakdown
| Component | Description |
|---|---|
H |
Static prefix indicating histogram data |
{Format} |
HT: High Throughput (IEEE 802.11n) NHT: Non-High Throughput |
{Channel} |
Single-letter identifier for the propagation scenario |
{Modulation} |
Integer label representing the modulation type |
{SNR} |
Signal-to-Noise Ratio in dB |
{SampleID} |
Unique sample index |
Modulation Label Mapping
The modulation field in the filename maps directly to the number of bits per symbol.
| Index | Modulation | Bits per Symbol |
|---|---|---|
| 1 | BPSK | 1 |
| 2 | QPSK | 2 |
| 4 | 16-QAM | 4 |
| 6 | 64-QAM | 6 |
Notes
All samples are stored in MATLAB
.matformat.Histograms are generated from raw IQ captures.
The nested folder structure makes it easy to create:
- train/validation/test splits by channel
- SNR-specific subsets
- modulation-balanced experiments
Citation / Attribution
If you use this dataset in academic work, please cite the associated publication or repository and include attribution under the CC BY-NC 4.0 license. DOI will be available soon
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