# Data-Driven Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
## 3 Experimental Setup and Dataset
### Measurement System and Methodology  
The data used in this work were collected as part of a large scale measurement campaigns on the cellular networks available in the city of Rome, Italy, performed between the end of 2020 and the beginning of 2021. The campaign was organized in subcampaigns, simply referred to as campaigns below, and carried out by using the Rohde & Schwarz (R&S) TSMA6 toolkit [46].  
The R&S TSMA6 is an integrated system including a spectrum scanner and a laptop. In the setup adopted for the present paper, the spectrum scanner was embedded with a Radio Frequency (RF) omnidirectional antenna, and used for continuous passive monitoring of downlink control signals from operative 3 GPP technologies, i.e., 5G NR, LTE, and Narrowband Internet of Things (NB-IoT). A laptop was used to run the R&S software, named ROMES, that allows for visual inspection of the ongoing campaign and for the collection of the measurements for subsequent analyses. A synchronized Global Positioning System (GPS) antenna was used for geolocating the measurements being collected. Note that other non-mobile networks cannot interfere in the 5G mid-band because the spectrum is licensed and dedicated to 5G NR; however, in case of any interference from other networks, the scanner has internal algorithms to suppress it. The TSMA6 has a time resolution of 400\(ns\) given a good time reference (e.g., a connected Global Navigation Satellite System (GNSS) Antenna with good reception), while the estimation of the uncertainty of measurements is less than 1.5 dB. The R&S TSMA6 scanner is also significantly faster and more sensitive than a traditional spectrum analyzer in terms of the minimum quality required for the measurement; the scanner is in fact able to detect the multipath even in low SNR conditions i.e., \(SNR\geq-5\) dB [47]. Overall, the TSMA6 passive scanner is a system with high measurement accuracy, proposed by R&S as viable solution for accurate Electromagnetic Field measurements without the need of user calibration [48]. The R&S TSMA6 Autonomous Mobile Network Scanner with R&S ROMES4 software used in this work has been indeed adopted in 5G measurement campaigns reported in several recent scientific publications. In [49; 50], the auto-calibration performed by the hardware was deemed sufficient to provide accurate channel measurements, and in [51] the power measurement accuracy of the TSMA6 was externally verified, reporting no need for additional calibration. In [52] the authors compared the data on 5G antenna placement obtained from a war-driving campaign using the TSMA6 with databases of 5G antennas available at a regulatory entity database, reporting a good accuracy of the TSMA6.  
This work takes advantage of the following key TSMA6 features: (a) Automatic Channel Detection (ACD), which enables the automatic detection of operative 3 GPP technologies in the spectrum bands under investigation, (b) BS positioning, which allows for estimating the position of the detected cellular BSs, and (c) MPC extraction algorithm, a built-in algorithm in TSMA6 that provides the detail of MPC for each CIR sample i.e., power associated to each MPC and its corresponding delay. Note that cellular BSs are most often referred to in terms of their PCIs or other identifiers (e.g., the identifier of the evolved Node B (eNB) for LTE), which altogether allows for their unique identification.  
A set of passive measurements was collected via the spectrum scanner to be used for investigating channel propagation properties. As a matter of fact, active measurements were also collected during the campaign, by connecting a 5G commercial device (Samsung S20) to the TSMA6 and having the device run Quality of Service (QoS) and Quality of Experience (QoE) performance tests, in particular delay, throughput, and video streaming tests. Active measurements are, however, beyond the scope of this paper; further details can be found in [53].