# Performance Analysis of Downlink 5G Networks in Realistic Environments
## 6 Simulation Results with Discussion  
Numerical findings were created using MATLAB R2013b and MOSEL-2 simulations based on the parameters listed in Table 2. There are four groups of figures: the capacity and performance of 5G cells in a single-service scenario are the subjects of the first set of findings (Figures 6-13). The second set of findings (Figures 14-27) examines 3G cell \begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline Average packet size-(Pareto distribution) & 480 bytes \\ Average requested file size (25 \(\times\) 480 bytes)-(Pareto distribution) & 12 Kbytes \\ Average number of packet calls within a session-)-(Pareto distribution) & 5 \\ Average reading time between packet calls)-(Pareto distribution) & 412 s \\ Average amount of packets within a packet call-(Pareto distribution) & 25 \\ Average inter-arrival time between packets)-(Pareto distribution) & 0.0625 \\ Number of codes (N) & 64 \\ Frequency, f & 20 GHz \\ Height of the mobile, hm & 1.5 m \\ Base station height, hb & 50 m \\ Service Factor, S(SF/SINR) & 2–128 \\ The cell radius r & 0–20 Km \\ Spreading factor (SF) & 32, 64, 128, 256 chips/symbol \\ Maximum transmission power (Psmax) & 120 W \\ Thermal Noise, N0 & \(-103\) dBm \\ Signal-to-interference noise ratio (SNR) & 2 dB \\ Interference factor, \(\varepsilon\) & 0.30–0.70 \\ Wavelength, \(\lambda\) & 0.15 m \\ Number of zones & 3 \\ Ratio of web browsing & 0.60 \\ Ratio of streaming & 0.30 \\ Ratio of voice over 5G & 0.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters [44]. performance and capacity in a multiservice case. The third group of results shows the network performance with multiservice cases and mobility (Figures 28-36). The last groups of two figures (Figures 37 and 38) are comparative results to compare the performance of the proposed algorithm in this research with a similar work in the literature [30]. Based on the developed equations for each environment, Figure 6 shows route loss under various propagation conditions. It is evident that minimal loss values are attained in a free-space environment where there is an unobstructed line of sight between the transmitter and receiver. Additionally, losses are seen to be larger in rural regions than in open spaces, especially at distances greater than 5 km, as opposed to the free-space model, where there is a clear line of sight between the transmitter and receiver. Rural locations can also have airports and buildings, unlike free spaces, but they tend to have fewer people. Due to their high population density and packed building stock, dense metropolitan areas typically experience the highest path losses and hence suffer from signal radiation. Figure 7 shows the maximum distance separation from Node B for various service factor values. The data rate increased with a smaller service factor, whereas the coverage area decreased. As shown in Figure 7, the service only covers approximately 40 customers when S = 8, and these customers are located within a range of 6 km from Node B. In contrast, if S is 128, a round distance of 22 km can cover more than 500 users. The link between the cell capacity and cell radius is illustrated in Figure 8, along with the impact of various service characteristics. As the cell radius is extended, it can be observed that at a larger value of S (S = 128), the capacity of the cell is maximized because many users can be accommodated. This graph demonstrates the positive correlation between the value of S and the cell radius measured from one side as well as the positive impact of this relationship on the cell's overall capacity. The figures (Figures 8-10) show similar behavior, but the goal is to show how the environment affects cell capacity. Higher S values increase system coverage and capacity.