## 5 Results
### Revisit Time and Data Transmission Analysis  
The average revisit time (\(R_{\text{avg}}\)) and maximum revisit time (\(R_{\text{max}}\)) are crucial metrics for evaluating the service quality of satellite-based communication systems. Figures 15-17 illustrate the average revisit time, maximum revisit time, and daily data transmission volumes for three LPWAN communication technologies (NB-IoT, LoRa, and Mioty) and three orbital configurations (600 km, 300 km, and 200 km) optimized using a genetic algorithm (GA) across four ground stations (Seoul, Oslo, Berlin, and Houston), as well as their overall averages. Figure 12: LEO evolution of best total number of satellites. Figure 15 shows that the VLEO (300 km)-LoRa constellation achieves the shortest average revisit time, while the VLEO (200 km)-Mioty constellation exhibits the longest. Despite these differences, all configurations satisfy the target performance criterion of maintaining an average revisit time below 60 min. Notably, the Oslo ground station records a significantly shorter revisit time compared to other stations, which is likely attributed to its higher latitude and the resulting increased frequency of satellite passes. In Figure 16, the variation in maximum revisit time is presented. The LEO-NB-IoT constellation demonstrates the lowest maximum revisit time, closely followed by the VLEO (300 km)-LoRa and VLEO (300 km)-Mioty configurations. Overall, the VLEO (300 km) configuration appears to be the most effective in minimizing maximum revisit times across the evaluated scenarios. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Group** & **Inclination (\({}^{\circ}\))** & **Number of** & **Satellites** & **Phase** & **Total** & **GA** \\  & & **Planes** & **per Plane** & **Difference** & **Satellites** & **Outcome** \\ \hline LEO-NB-IoT & 59.70/63.89 & 16/1 & 4/1 & 13/0 & 65 & 335.95 \\ LEO-LoRa & 68.34/37.02 & 11/1 & 5/2 & 9/0 & 57 & 310.60 \\ LEO-MiOTY & 36.09/62.31 & 2/13 & 1/5 & 1/3 & 67 & 387.04 \\ VLEO (300 km)-NB-IoT & 50.01/62.31 & 4/13 & 1/4 & 3/5 & 56 & 322.68 \\ VLEO (300 km)-LoRa & 35.06/58.60 & 4/16 & 1/3 & 3/10 & 52 & 279.74 \\ VLEO (300 km)-MiOTY & 61.44/40.30 & 14/1 & 4/2 & 13/0 & 58 & 332.69 \\ VLEO (200 km)-NloT & 41.02/66.97 & 5/14 & 1/5 & 4/13 & 75 & 383.86 \\ VLEO (200 km)-LoRa & 38.65/62.56 & 6/9 & 1/5 & 0/8 & 51 & 299.82 \\ VLEO (200 km)-MIOTY & 58.33/67.91 & 3/17 & 1/3 & 1/3 & 54 & 332.85 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Final genetic algorithm results for optimized satellite deployment. Figure 14: VLEO (200 km) evolution of best total number of satellites. Figure 13: VLEO (300 km) evolution of best total number of satellites. Figure 17 displays the daily data transmission volumes for each ground station. The VLEO (300 km)-NB-IoT configuration achieves the highest transmission volume, which can be attributed to NB-IoT's higher bit rate. In contrast, the LoRa and Mioty configurations yield relatively lower transmission volumes, with LoRa slightly outperforming Mioty. These results indicate that NB-IoT is best suited for high-data-rate applications, while LoRa offers marginally better efficiency compared to Mioty. In summary, these findings confirm that the GA effectively optimizes satellite constellation configurations. The VLEO (300 km) configuration, particularly when paired with LoRa, provides superior performance across key metrics. Moreover, NB-IoT exhibits enhanced performance in LEO and VLEO (300 km) environments compared to VLEO (200 km), and Mioty achieves its best performance in the VLEO (300 km) configuration. Overall, the results underscore the importance of carefully balancing coverage, revisit time, and data transmission efficiency to achieve a cost-effective and robust satellite deployment strategy. Additionally, to analyze revisit time variations by latitude, measurements were taken at 5\({}^{\circ}\) intervals along the latitude direction with the longitude fixed at 0\({}^{\circ}\). Figures 18-20  
Figure 16: Maximum revisit times of ground stations.