NISPMar 18

Curated Wireless Datasets for Aerial Network Research

arXiv:2510.0875218.95 citationsh-index: 13
AI Analysis

This provides a resource for researchers working on aerial network problems, though it is incremental as it focuses on curation rather than new data or methods.

The authors consolidated publicly available aerial wireless measurement datasets collected using AERPAW, organizing them under a unified taxonomy with harmonized metadata and verified access. This curated catalog supports propagation modeling, machine learning, localization, and system-level evaluation for 5G-Advanced and emerging 6G aerial networks.

This Review consolidates publicly available aerial wireless measurement datasets collected using AERPAW. We organize signal-level, power-level, and KPI-level datasets under a unified taxonomy, harmonize metadata, and provide verified access with reproducible post-processing scripts. The curated catalog supports propagation modeling, machine learning, localization, and system-level evaluation for 5G-Advanced and emerging 6G aerial networks.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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