Reusable 5G Private Campus Network Dataset: Configuration, Extraction, and Application

In the current literature, the measurements on deployed and operational Fifth-Generation (5G) networks are still lacking. This study offers a dataset of New Radio (NR) signal measurements made using the RPTU Kaiserslautern’s private campus 5G network as well as other public 5G networks to close this gap. The dataset includes measurements of signal strengths such as Synchronization Signal Reference Signal Received Power (SS-RSRP) and Synchronization Signal Signal-to-Interferenceplus- Noise ratio (SS-SINR) of serving cells, as well as signal strengths of the neighboring public 5G Standalone (SA) and Non-Standalone (NSA) networks, i.e., within the perimeter of the campus. The measurements described here are taken at various indoor and outdoor locations using the Rohde & Schwarz’s (R&S) TSME6 and TSMA6 scanners. The primary goal of the dataset is to allow researchers to reuse data from the 5G SA live network in understanding the radio access network (RAN) and Physical Layer characteristics of the network and use them for machine learning purposes to optimize the network. In addition to this data, several areas where the data can be used for learning and optimization tasks in the network are provided.