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<p>This Data Descriptor presents a fifth-generation (5 G) macrocell signal dataset collected through unmanned aerial vehicle (UAV) and ground surveys in a 9 km² complex terrain environment. The released data include raw measurement records, processed grid data, and base-station information provided by the network operator. The raw records contain Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Global Navigation Satellite System (GNSS) coordinates, altitude, timestamps, and cell identifiers. The grid dataset contains 10,000 cells and integrates Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), building morphology, base station attributes, and engineered variables, together with grid center coordinates and observation or interpolation labels. Compared with our previous model-focused study, this work releases the underlying measurements, base station records, metadata, data dictionaries, and loading scripts. The dataset supports reproducible 5 G propagation analysis, radio environment mapping, and machine learning benchmarking in complex terrain scenarios.</p>

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A Real-time 5G Macro-cells Signal Dataset for Signal Model Simulation and Prediction within Complex Terrain Area

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月30日

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  • Tingting Xu,
  • Nuo Xu,
  • Yapeng Xu,
  • Wei Yang

摘要

This Data Descriptor presents a fifth-generation (5 G) macrocell signal dataset collected through unmanned aerial vehicle (UAV) and ground surveys in a 9 km² complex terrain environment. The released data include raw measurement records, processed grid data, and base-station information provided by the network operator. The raw records contain Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Global Navigation Satellite System (GNSS) coordinates, altitude, timestamps, and cell identifiers. The grid dataset contains 10,000 cells and integrates Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), building morphology, base station attributes, and engineered variables, together with grid center coordinates and observation or interpolation labels. Compared with our previous model-focused study, this work releases the underlying measurements, base station records, metadata, data dictionaries, and loading scripts. The dataset supports reproducible 5 G propagation analysis, radio environment mapping, and machine learning benchmarking in complex terrain scenarios.