# Data-Driven Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
## 1 Introduction  
The Third Generation Partnership Project (3 GPP) recently defined the New Radio (NR) standard of Fifth Generation (5G) cellular networks [1, 2], which promises to accommodate higher data rates, low latency, and massive device connectivity. The 5G NR supports a large variety of use cases and services compared to 4G Long Term Evolution Advanced (LTE-A), thanks to its numerous new features. In particular, 5G use cases include enhanced Mobile Broadband (eMBB) [3], Ultra-Reliable Low Latency Communications (URLLC) [4], and massive Machine-Type Communications (mMTC) [5]. Applications that benefit from the existence of a 5G network include autonomous vehicles, smart transportation, smart factories, agriculture, virtual and augmented reality, smart grids, and healthcare [6, 7, 8]. Frequency wise, 5G systems operate in the so-called _low-band_, _high-band_, and _mid-band_ spectrum portions [9]. The low-band extends up to 2 GHz, while the high-band includes frequencies from 6 GHz and up, e.g., millimeter wave bands (mm-wave). The mid-band (refers to frequencies between 1 and 6 GHz) lies in between low and high bands; it has gained much attention lately because it offers a good balance between network capacity and coverage [9; 10]. As a matter of fact, a large number of commercial 5G networks currently being deployed rely on the mid-band, and in particular on the 3.3-3.8 GHz portion, called Band n78 [11; 12; 13; 14; 15]. It is thus relevant to understand signal propagation properties in the mid-band in order to develop high-performing 5G networks. As is well known, a signal may reach a receiver through multiple paths, due to reflection, diffraction, and scattering. Hence, a signal typically experiences both small and large scale variations in power over time. This is particularly true in indoor environments, where human activities and objects of different material, size, and geometry, affect the radio propagation significantly, eventually leading to highly dynamic propagation conditions [13; 14; 16; 17]. Incidentally, several 5G use cases target indoor scenarios, such as smart buildings with different types of sensors, factory automation, remote control of robotic machinery, and automated vehicles in logistic applications, to mention a few [18; 19; 20; 21]. This supports the need for an understanding of how current 5G deployments, formed by traditional outdoor base stations (BSs), provide coverage and connectivity in indoor environments. As a result, several works dealing with the empirical characterization of the indoor channel propagation at the 5G mid-band were recently carried out [6; 10; 11; 12; 13; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31]. In these works, the analysis was mostly based on measurements performed on dedicated, single-link testbeds, which typically did not take into account the impact of beamforming strategies, in particular single wide-beam vs. multiple SSB-based; a detailed discussion on single wide-beam and multiple SSB-based 5G strategies is given in Section 2.2. In addition, none of the existing studies provided a systematic study of the correlation between the parameters that characterize channel propagation. Within this context, the present paper provides the first empirical characterization of the outdoor-to-indoor propagation experienced in commercial 5G mid-band systems (in particular in Band n78) deployed in urban scenarios, based on channel measurements obtained using the Rohde&Schwarz TSMA6 Mobile Network Scanner, capable of detecting SSBs for all 5G operators within coverage and decoding the content corresponding Physical Broadcast Channel (PBCH)/Master Information Block (MIB). The study carries out an exhaustive analysis of all the relevant time- and power-related parameters characterizing channel propagation, taking into account the impact of beamforming strategies, and also includes a comprehensive correlation analysis of the parameters. The paper is organized as follows. Related work, motivation, and contributions are analyzed and discussed in detail in Section 2.