USC Drone-Based Channel Measurement Data

This 3.5 GHz drone-based wireless channel measurement dataset, collected at the University of Southern California (USC), spans a 200 m \u00d7 200 m outdoor area and is designed to support research in next-generation wireless systems. The dataset contains large-scale channel measurements in realistic outdoor environments, where a drone-mounted transmitter emulates an aerial access point. In total, more than 30,000 drone positions were captured, along with 128 ground user positions organized into clusters.The dataset enables a wide range of studies in beyond-5G and 6G systems, including:Cell-free massive MIMO system tradeoffs comparing concentrated versus semi-distributed versus fully-distributed antenna deployments,Spatial non-stationarity and its impact on multi-antenna system design,Air-to-ground propagation characteristics within non-terrestrial networks,Path loss modeling and large-scale channel statistics in outdoor environments.By offering a comprehensive and well-documented measurement campaign, this dataset provides the community with a benchmark resource for validating theoretical models, evaluating algorithms, and guiding the design of robust next-generation wireless networks. It is intended to support both academic research and industrial development, bridging the gap between theoretical analysis and practical deployment insights.