Dataset Artifacts

5G NVIDIA Aerial Testbed SRS Indoor and Outdoor Dataset

Max Mayershofer

Florian Kaltenberger

Omid Esrafilian

Reem Bahsoun

This dataset contains raw Channel Frequency Response (CFR) measurements collected from uplink Sounding Reference Signals (SRS), the corresponding FAPI metadata, and the slot of fronthaul (FH) IQ samples where SRS was transmitted by a 5G User Equipment (UE). Data is provided for real-world multi-antenna 5G indoor and outdoor deployments using the Aerial Testbed at the EURECOM campus in scenarios with and without a dynamic scatterer present. In the indoor scenario this is a person walking through the cell, while in the outdoor setting it is a UAV/drone flying through the cell.

5G SRS Indoor Positioning Dataset

Ping-Yu Hsieh

Chieh-Chun Chen

This dataset contains pre-processed spatial features extracted from uplink Sounding Reference Signals (SRS) in a 5G ISAC (Integrated Sensing and Communication) indoor environment. Utilizing a O-RAN setup, it provides real-time extracted CIR taps, frequency-domain amplitudes, and spatial footprints to enable AI/ML-driven localization and human-blockage detection.

5G SRS Outdoor Dataset

Mohsen Ahadi

Florian Kaltenberger

Omid Esrafilian

Adeel Malik

This dataset contains raw Channel Impulse Response (CIR) measurements collected from uplink Sounding Reference Signals (SRS) transmitted by a 5G User Equipment (UE) in a real-world outdoor deployment at the EURECOM campus. The dataset enables research on localization, positioning, channel charting, and AI/ML-driven wireless network analysis using multi-antenna 5G measurements.

RAN KPI and Configuration Dataset

Ali Yaghoubian

This dataset contains 1-second–granularity time-series measurements collected from a 5G laboratory testbed operating on band n78. It combines detailed RAN configuration parameters (e.g., center frequency, and TDD patterns) with key MAC-layer KPIs such as ACK/NACK statistics, bitrate, MCS, etc. The dataset is intended for research and development tasks including configuration-to-KPI modeling, RAN tuning and optimization, and control algorithm evaluation.

Interference Anomaly Detection Dataset

Mohamed Ali Msadek

This dataset provides 1-second–granularity time-series measurements collected from a dedicated 5G Standalone (SA) testbed operating on band n41. It includes multi-layer RAN telemetry (MAC, RLC, PDCP) under both nominal conditions and intentionally induced persistent uplink interference, enabling reproducible anomaly detection, cross-layer analysis, and machine learning research.