# Data Traffic Modeling in RPAS/UAV Networks with Different Architectures
## 4 Models  
In our previous works [32; 33] models of communication channels \"Base Station-to-RPAS\" and \"Base Station-to-Satellite-to-RPAS\" were built on the basis of 3 GPP Wideband Code Division Multiple Access (WCDMA) Standard. Using the MATLAB software, quantitative characteristics of the channels were obtained taking into account the Multipath Rayleigh Fading, the nonlinearity of the satellite transponder, various antenna diameters, and RPAS speeds. In this work, within the framework of the RPAS-assisted cellular communication paradigm, we first developed models with different architectures for simulating the traffic of Base Station (BS) data exchange with user cellular networks using RPAS. The BS can be ground or air with two-way traffic both in the control channel and in the payload channel in all models. Flying RPASs have access to cellular infrastructure from the sky. This paradigm allows the establishment of reliable wireless communications with ground cell sites. It is assumed that the BS will not simultaneously work with terrestrial users within the radio Line of Sight (LoS). Flying RPASs should have antennas with radiation patterns that provide three-dimensional coverage for communications with the BS, ground cellular network and other RPASs. Integration of RPASs into a cellular network must provide the necessary QoS, coverage and data transfer rates of the existing cellular network. The proposed model architectures, due to the dynamic mobility and movement of the RPAS, provide many advantages to the existing ground communication system. The flying BS or relay can be provided as required upon request of 5G/B5G cellular systems, which is an attractive operational solution in emergencies, disasters, and search and rescue operations. The RPAS team reliably communicates directly with each other to monitor autonomous flight behavior and prevent collisions in swarms. This architecture is illustrated by the example of Models 2, 3, and 4 (Figure 2). The models' architecture was based on ICAO document [23] and included BS, RPASs, and Cellular Users (CUs). All models (Figure 2) were designed using Professional NetCracker 4.1 software [35] and their parameters are given in Table 1.  
In Model 1 \"BS-RPAS1-CU3\", the BS controls RPAS1 in LoS, and through it communicates with the cellular network, represented by three users. In all models, networks containing 1, 3, 5, and 7 users were considered, but in this work, for simplicity, data are given for only three users for each RPAS, which does not limit in any way the generality of the consideration. In Model 2 \"BS-RPAS1-RPAS2-CU3\", the BS communicates with the cellular network through two RPASs, which increases coverage and reveals the impact of the second RPAS on data traffic. Model 3 \"BS-RPAS1-CU3-RPAS2-CU3\" adds users to RPAS1 for simulation of traffic ramification to work with more users and increase the BS coverage. Model 4 \"BS-RPAS1-CU3-RPAS2-CU3-RPAS3-CU3\" considers an even more complex architecture with an addition of RPAS3 and CU 3, which further increases the BS coverage and increases the load on RPAS1 (Figure 3). All wireless connections of the BS, RPASs and CUs are selected to be 10 km. Figure 2: Architecture of models: (**a**) Model 1; (**b**) Model 2; (**c**) Model 3; and (**d**) Model 4. The wireless architecture of connecting the BS to the RPAS1 and each of the RPAS to the CU results in more reliable LoS channels. In addition, our models incorporate RPASs space diversity to reduce mutual interferences. In reality, there are effects such as fading, shading and loss along the way that should be considered. Only the free-space channel model lacks fading and shading effects and is suitable for rural areas where the LoS assumption is valid for high-altitude RPAS and ground stations. However, in urban environments, low-altitude RPAS can detect channels other than LoS. Therefore, it is necessary to look for ways to properly match the propagation conditions taking into account the propagation loss in space.