## 1 Introduction  
This paper extends our conference paper significantly [1]. Cellular wireless infrastructure has served as the standard data transmission system in recent decades. However, the expected growing demand for internet services, high speed, wide bandwidth, and availability requires a significant change in communication infrastructure, deployment, technology, and management. Free-space, high-speed communications, employing numerous satellites and related ground stations, seem to reasonably fulfill this extreme demand. High frequencies are considerably affected by rainfall that attenuates the propagating signal at microwave and millimeter-wave frequencies. Therefore, mitigating rain attenuation is required to ensure the quality of microwave and millimeter-wave links. Dynamic attenuation mitigation methods can be implemented alongside attenuation prediction models. Calculating the impact of rain on satellite communication relies on attenuation data collected for each ground station and transmission frequency. These data enable us to estimate the expected attenuation per location with standard prediction methods. The availability of satellite beacon measurements has provided a database for validating and refining the prediction models. The predicting techniques recommended by the ITU-R assume that an equivalent cell of uniform rainfall rate can model the non-uniform rainfall along the propagation path. An identical, cylindrical cell of constant rain can intercept the link at any position with equal probability. A practical path length is calculated as the average length of the intersection between the cell and the propagation path. As a result, the effective path length is always smaller than the actual path length. In the slant path prediction method, horizontal and vertical reduction factors consider the spatial and temporal variability of the rain field. A satellite cruises in a specific orbit while receiving and sending signals to and from a ground station. The ground station is located in a fixed location. Figure 1 depicts the entire satellite communication scene where the ground station, satellite, and orbit are synchronized to enable data transmission between them. The signal route from the satellite to the ground station contains two main sections: from satellite to near ground, designated as A; and from close land to the ground station, designated as B. Section A focuses on predicting the attenuation level of signals from the satellite, passing the free space up to the ground buildings. Section B indicates the remaining signal strength after passing the ground station's blocking structures. Sections A and B complement each other to predict the initial signal strength by satellite to overcome the accumulated signal attenuation when passing both sections. The satellite link budget \(LB\) is distributed among the panels, including the \(P_{T}\) transmitter output power (dBm), \(G_{T}\) transmitter antenna gain (\(dBi\)), \(G_{R}\) receiver antenna gain (\(dBi\)), \(L_{FS}\) free-space propagation loss, and \(L_{M}\) (=\(L_{S}+L_{R}\)) miscellaneous losses (fading margin, body loss, polarization mismatch, and other losses) (dB). The link budget can be expressed as \(LB=P_{T}+G_{T}+G_{R}+L_{FS}+L_{M}\) and \(\text{SNR}=\frac{PT\cdot GT\cdot GR\cdot LFS\cdot LM}{N_{0}\cdot B}\) where \(N_{0}\) is the basic noise level, and \(B\) is the signal bandwidth. To maintain an SNR that ensures the maximum transmission rate when the signal attenuation changes (\(L_{M}\) decreases or increases), the transmission output power \(P_{T}\) is changed accordingly. Figure 2 depicts the components used for calculating the \(LB\) value. We used the STK simulator to obtain synthetic communication data between the satellite and the ground station according to different weather-situation data to prove our approach. Typical ground stations in modern urban areas are surrounded by high buildings disturbing the propagation of electromagnetic waves.