Published December 1, 2025 | Version 1.0.0
Dataset Open

LoRaIQ: Experimental LoRa Dataset with Annotated IQ Samples

  • 1. ROR icon École Polytechnique Fédérale de Lausanne

Description

Summary

This dataset contains more than 75,000 LoRa frames recorded within and around the EPFL campus in Lausanne, Switzerland. The measurements were collected using four remote radio heads (RRHs) installed on campus rooftops.

Each entry provides all information required for synchronization, demodulation, and decoding of a single LoRa frame. Every frame is accompanied by an IQ sample file following the standard SigMF [1] specification, along with its corresponding metadata (annotations).

Dataset Details

Recordings were captured by four RRHs located at the positions shown in Fig. 1. Each RRH consists of a USRP-2920, a Raspberry Pi 5, and a Quectel L80 GPS receiver. The deployment captures a wide range of propagation scenarios due to differing elevations, line-of-sight conditions, and urban obstructions within the campus environment.

The dataset features transmissions from a unmanned aerial vehicle (UAV) and a pedestrian-carried transmitter, with transmitter velocities between 0 and 5.6 m/s. Measurements are grouped for three representative scenarios:

  • UAV line-of-sight (LoS)
  • UAV non-line-of-sight (NLoS)
  • Pedestrian NLoS

The transmitter parameters used during data collection are summarized below:

Frequency        862.5 MHz Spreading Factor       7 | 10
Coding Rate    4/5 Bandwidth                  125 | 250 kHz
Tx Power         14 dBm Payload Length          7 | 19 B

Note: Boldface values indicate the parameters used for the UAV-mounted transmitter.

In addition to all synchronization parameters required for demodulation, such as carrier frequency offset, reception timestamp, and LoRa PHY parameters, each frame also includes the transmit location, transmit payload, and an SNR estimate.

Dataset Entry 

All the keys of the dataset.csv is indicated below and Fig. 2 illustrates the spectrogram of one received  frame opened with Inspectrum [2], showing the LoRa chirps with annotations.

sf cr fc bandwidth payload_base64 rrh_idx rx_sample_rate rx_timestamp_full
rx_timestamp_frac cfo snr latitude longitude velocity target_velocity name
transmission_idx area_type sigmf_file sigmf_file_offset sigmf_file_n_samples sigmf_file_start_time_full

sigmf_file_start_time_frac

 

 

File Structure

  • dataset.csv                                        (Dataset with all frame descriptions)
  • load_and_plot_samples.py             (Exemple to load IQ samples)         
  • rrh_locations.md                              (GPS positions of the four remote radio heads)
  • zenodo_description_figures.png     (An illustration shown on Zenodo description page)
  • sigmfs                                                (Folder containing the raw IQ samples)
    • <Date and time of measurement 1>
      • RRH1
        • 1.sigmf-data
        • 1.sigmf-meta
        • 2.sigmf-data
        • 2.sigmf-meta
        • ...
      • ...
      • RRH4
        • 1.sigmf-data
        • 1.sigmf-meta
        • 2.sigmf-data
        • ...
    • <Date and time of measurement 2>
      • ....

Contact

For any questions related to this dataset, please contact joachim.tapparel@epfl.ch.

References

[1] "SigMF specification,'' Accessed: Dec 1, 2025. [Online]. Available: https://sigmf.org/

[2] "Inspectrum", Accessed: Dec 1, 2025. [Online]. Available: https://github.com/miek/inspectrum

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Additional details

Dates

Created
2025-12-01