# Channel Model for Estimating Received Power Variations at a Mobile Terminal in a Cellular Network
## 3 Experimental Measurements Conducted in a Cellular Network
### Urban Environment  
The study was carried out in an urban area situated in the northeastern part of Ecuador's capital, specifically in the \"La Carolina\" neighborhood within the Iriaquito parish, as shown in Figure 5. Notably, this area has a high density of base stations per km\({}^{2}\). Upon completing data collection, it was identified that a total of fourteen eNBs were involved in handover processes.  
This sector also includes major business, financial, and commercial centers, as well as green spaces, which implies that the line-of-sight (LoS) between the mobile terminal and the connected base station is not always guaranteed. Furthermore, during data collection across various locations, obstacles such as buildings, vehicular traffic, and other environmental factors were encountered, potentially affecting the measurement process.  
Table 1 summarizes the population characteristics of the two environments analyzed in this study.  
Data collection was carried out in two directions: on one day, starting from Point 1 and ending at Point 2, and on another day, starting from Point 2 and finishing at Point 1. This approach was chosen to facilitate the application of vector calculus during the data processing stage.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parish** & **Neighborhood** & **Area (Ha)** & **Area (km\({}^{2}\))** & **Population (Inhabitants/Ha)** \\ \hline Urban (Iriaquito) & La Carolina & 11,369 & 2.70 & 30,696 \\ Suburban (San & & & \\ Pedro de & Rumiloma & 30,000 & 3.00 & 12,700 \\ Taboada) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Population indicators of the area of interest.  
Figure 5: “La Carolina” neighborhood, Iriaquito parish.  
The selected routes for data collection in the aforementioned area are shown in Figure 6.  
The set of routes was selected based on several key objective criteria: the density of mobile service antennas for the specific operator in Ecuador, the occurrence of handover events during the connection to enable mobility analysis, the feasibility of data collection on foot, and ease of transportation. The latter was ensured by placing the start and end points of each route near metro stations, bus rapid transit (BRT) stops, or urban bus terminals, facilitating operator mobility and optimizing the measurement process. Additionally, the routes were chosen to cover diverse urban morphologies, guaranteeing spatial diversity and comprehensive signal sampling across the study area.  
Once the area of interest was defined, measurements were conducted at different times and on various days of the week to capture the temporal and spatial variability in network performance. The total number of samples collected per route was 11,981 for Route 1, 8396 for Route 2, and 12,738 for Route 3.  
During the preprocessing stage, the dataset was cleaned to remove inconsistencies such as invalid base station identifiers, geographic coordinates outside the area of interest, unrealistic power values, and samples missing essential attributes.  
After compiling the cleaned dataset, the measurement routes were plotted in QGIS on a color-coded map according to their cell identifiers. Each triangle on the map represents one of the 14 base stations operating in the area, encompassing a total of 59 cells with useful information. The measurement points are colored based on their associated base station, as illustrated in Figure 7.  
Figure 6: Selected routes for data collection and base stations in the urban area.