Reusable 5G Private Campus Network Dataset

In the current literature, the measurements on<br> deployed and operational Fifth-Generation (5G) networks are<br> still lacking. This study offers a dataset of New Radio (NR) signal<br> measurements made using the RPTU Kaiserslautern’s private<br> campus 5G network as well as other public 5G networks to close<br> this gap. The dataset includes measurements of signal strengths<br> such as Synchronization Signal Reference Signal Received Power<br> (SS-RSRP) and Synchronization Signal Signal-to-Interference-<br> plus-Noise ratio (SS-SINR) of serving cells, as well as signal<br> strengths of the neighboring public 5G Standalone (SA) and<br> Non-Standalone (NSA) networks, i.e., within the perimeter of the<br> campus. The measurements described here are taken at various<br> indoor and outdoor locations using the Rohde &amp; Schwarz’s<br> (R&amp;S) TSME6 and TSMA6 scanners. The primary goal of the<br> dataset is to allow researchers to reuse data from the 5G SA live<br> network in understanding the radio access network (RAN) and<br> Physical Layer characteristics of the network and use them for<br> machine learning purposes to optimize the network. In addition<br> to this data, several areas where the data can be used for learning<br> and optimization tasks in the network are provided.当前学术文献中，针对已部署并投入运营的第五代（5G）网络的实测数据仍较为匮乏。为填补这一研究空白，本研究构建了一套新空口（NR）信号实测数据集，采集自莱茵兰-普法尔茨技术大学（RPTU）凯泽斯劳滕分校的私有校园5G网络，以及多座公共5G网络。该数据集包含服务小区的信号强度实测数据，具体为同步信号参考信号接收功率（SS-RSRP）与同步信号信干噪比（SS-SINR）；同时收录了校园范围内邻接公共5G独立组网（SA）与非独立组网（NSA）网络的信号强度数据。本次实测采用罗德与施瓦茨（R&S）TSME6与TSMA6信号扫描仪，在多处室内与室外点位完成数据采集。本数据集的核心目标是为研究者提供复用5G独立组网商用网络数据的途径，以助力其深入理解该网络的无线接入网（RAN）与物理层特性，并将相关数据应用于机器学习任务，进而实现网络优化。除上述原始数据外，本研究还列举了该数据集可用于网络学习与优化任务的多个应用场景。