**2. Related Work**

In this section, we first review recent vendors' and standardization bodies' activities related to UAV integration into cellular 5G systems. We then proceed by providing an outlook of UAV LoS blockage models proposed over the last few years.

#### *2.1. UAV Integration into 5G*

In recent years, UAVs support in modern wireless networks has attracted attention from network operators and standardization organizations. The 3GPP TR 36.777 summarizes the research done on LTE support for UAVs. In particular, it considers several cellular network improvements for efficient service of UAV users, quantifies the impact of UAVs on the network, and evaluates characteristics of UAV-based service in urban and rural environments. Computer simulations of such systems, augmented with measurement data, show that the use of UAVs may lead to increased interference in both uplink and downlink directions. TR 36.777 also suggests methods to eliminate interference. Another issue identified in TR.36.777 is related to UAV mobility. The standard defines methods for providing additional information about the deployed ground network that can be used for decision-making during flight.

Since 3GPP Release 16, UAV support has been seen as a critical feature of the 5G cellular network infrastructure. In this context, TR 22.829 summarizes the use cases and analyzes UAV functions that may require enhanced support from access networks. It includes video broadcast applications, command and control services, and the use of UAVs as aerial BSs. The latter UAV application is covered in detail in TR 38.811.

3GPP is currently continuing research in this area. In particular, some of the tasks are to reduce the negative effects caused by the mobility of UAVs and to adapt to the needs of business, security, and the remote identification of UAVs. Specifically, TR 22.125 defines operational requirements for 3GPP systems. The 3GPP is expected to improve UAV integration methods in 5G communication networks in future revisions of TR 23.754 and TR 23.755. Nevertheless, it is already clear that UAVs will soon provide a wide range of services in 5G access networks.

#### *2.2. LoS blockage Probability*

The question of LoS occlusion by large static objects such as buildings has been significantly investigated in the context of terrestrial users. One of the fundamental studies dating back to 1984 [23] uses a methodology based on the combination of mathematical modeling and field measurements. Specifically, the study proposed a mathematical model describing a statistical method for predicting LoS propagation paths for a receiver-transmitter pair in densely populated areas based on a statistical building distribution model. The core of

the model is based on an analysis of the mean free path of moving particles in randomly distributed obstacles. The resulting LoS blockage probability was calculated for a scenario where buildings are located along a certain axis between the receiver and transmitter, with building heights distributed exponentially.

The work in [24] includes a description of a model for calculating the LoS blockage probability for a pair UE-BS in the Fresnel zone of a certain radius, applicable to typical European cities with dense and regular streets. This empirical model is based on empirical data from the city center of Bristol, UK. The model takes into account the height of the buildings, their dimensions, the width of the streets, and the distribution of street corners. The carried out numerical analysis demonstrated that the distribution and variance of building height has little impact on the LoS blockage probability. Furthermore, in [16], a random shape theory for modeling random blockage effects in urban cellular networks is utilized. A fundamental method has been established to determine the LoS blockage probability from irregularly placed buildings. Although no direct comparison with empirical measurements has been performed, the main finding was that the LoS blockage probability decreases exponentially fast with the link length. Another example of a similar model for terrestrial users is reported in [25], where cube-shaped structures with uniformly distributed height are utilized as a model for buildings. The authors report the LoS blockage probability in integral form.

Recently, a number of models for UAV LoS blockage probability have been reported. In [26], the authors carried out a large-scale simulation campaign based on real data taken from the city of Ghent for collecting UAV coverage data with both LTE and mmWave BS terrestrial deployments. The reported data highlights that mmWave NR coverage of UAV is insufficient even for the highly dense deployment of these BSs. In [27], a method to estimate LoS blockage probability based on a scanning laser is proposed. This methodology is applied to open parking situations to collect data and use them to form an exponentially decaying probabilistic LoS blockage model.

Both ITU-R and 3GPP have also defined their LoS blockage models for UAV. In particular, the ITU-R model, reported in [20], considers the frequency range from 20 to 50 GHz. The LoS blockage probability is calculated assuming that the terrain is flat and has a certain constant slope over the area of interest. The model also accounts for different heights of UE and BS and uniform distribution of the building height. The LoS blockage probability is produced in product-form. Contrarily, 3GPP models of LoS blockage defined in TR 38.901 are purely empirical, obtained by fitting the measurement data to the exponentially decaying function starting from a certain breaking point. The model specifically tailored to UAV and proposed in TR.36.777 [28] utilizes only two parameters: BS height and UAV altitude. Parameters such as the height of buildings, building density and others are not taken into account. Thus, the model can only be used for certain BS heights, significantly reducing the application scenarios.

Recently, the authors in [21] proposed a detailed and versatile UAV LoS blockage probability that accounts for most critical parameters including different UAV and BS heights, different building height distribution, and various widths of streets and building blocks. The standard city deployment is however limited to the regular one and captured by the Manhattan Poisson line process (MPLP). Owing to the model complexity, closed-form expressions have been provided for specific building height distributions only. The authors demonstrated that the LoS blockage probability is highly sensitive to the type of deployment, the distribution of building heights, and the flight altitude of the UAV. Also, according to the authors, the existing standardized models developed by 3GPP and ITU-R provides an overly optimistic approximation of the UAV LoS blockage probability.
