## 5 Simulation Results and Analysis
### Simulation Results  
Firstly, we establish the GEO/LEO heterogeneous satellite network constellation model. In order to be more realistic, we use some data from real satellites in the model. The position and coverage of GEO satellites refer to ChinaSat12, and the altitude of LEO satellites is close to that in Iridium satellite system. Parameters of the GEO/LEO heterogeneous network model are shown in Table 2.  
There are various communication scenarios in reality, such as marine environment monitoring, remote control in emergency rescue, Internet services in remote areas, etc. In different communication scenarios, the distribution of various types of services must be different. For example, the proportion of commands in emergency rescue must be larger. To increase the credibility of the results, we generated two distributions of services. The first distribution is that the proportion of delay-sensitive services is small, and the ratio of the quantity of the four services is 1:3:3:3 (grade1:grade2:grade3:grade4). In the second distribution, delay-sensitive services account for a larger proportion, and the ratio of the quantity of the four services is 3:3:2:2 (grade1:grade2:grade3:grade4). Figures 4 \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline GEO satellite orbital height & 35,786 km \\ Number of GEO satellites & 1 \\ Bandwidth of GEO satellite & 100 MHz \\ Number of subchannels in GEO satellite & 200 \\ LEO satellite orbital height & 765 km \\ LEO constellation type & Walker \\ Number of low Earth orbital planes & 6 \\ Number of LEO satellites in orbit & 6 \\ Bandwidth of LEO satellite & 50 MHz \\ Number of subchannels in LEO satellite & 50 \\ Antenna gain & 43.3 dBi \\ G/T parameter & 15 dB/K \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Satellite System Simulation Parameters. respectively show the simulation results of the average throughput, the average number of handovers, and forced termination probability of the system under these two scenarios, (a) the first service distribution of 1:3:3:3 (grade1:grade2:grade3:grade4) and (b) the second service distribution of 3:3:2:2 (grade1:grade2:grade3:grade4). We compare the average throughput of the four schemes under different user arrival rates. As shown in Figure 4, the system tends to be saturated when the user arrival rate reaches 7000 per hour. The Importance-TOPSIS scheme proposed in this paper has the best performance in average throughput, followed by the ordinary TOPSIS scheme with equal weights of all attributes. There is a slight difference between the Entropy-TOPSIS scheme and the SINR-max scheme in throughput, and the entropy weight TOPSIS method is slightly better. Figure 5 shows the number of handovers per minute at different user arrival rates. It can be seen that the Importance-TOPSIS scheme proposed in this paper has the least average handover times, followed by the ordinary TOPSIS scheme, and the Entropy-TOPSIS has the most average handover times. The SINR-max scheme is more likely to select the  
Figure 4: Average throughput of the satellite system under different schemes. (a) Service distribution 1, (b) Service distribution 2. Figure 5: The number of handovers under different schemes. (a) Service distribution 1, (b) Service distribution 2.  
same satellite in several consecutive selections, and the handover time is less than that of the Entropy-TOPSIS scheme. The Entropy-TOPSIS scheme considers the entropy of each attribute value of candidate satellites when setting the weight. It can be seen that this weight setting method is not helpful in reducing the handover times. Figure 6 shows the forced termination probability, which is the probability of a call being dropped during the communication of different services grades when the user arrival rate is 5000 per hour. The Importance-TOPSIS scheme has the best performance in the forced termination probability, the other three schemes have similar forced termination probability, and the SINR-max scheme is slightly worse.