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Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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LoRaIQ: Experimental LoRa Dataset with Annotated IQ Samples

Authors: Tapparel, Joachim; Burg, Andreas;

LoRaIQ: Experimental LoRa Dataset with Annotated IQ Samples

Abstract

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) RRH1 1.sigmf-data 1.sigmf-meta 2.sigmf-data 2.sigmf-meta ... ... RRH4 1.sigmf-data 1.sigmf-meta 2.sigmf-data ... .... 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

Keywords

UAV, C-RAN, IQ samples, LoRa

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average