# Caching-Aware Intelligent Handover Strategy for LEO Satellite Networks
## 4 Results  
Satellite tool kit (STK) is used to obtain the topology of the satellite network. The simulation parameters are shown in Table 2. And the number of visible satellites for each terrestrial user is from 2 to 4, which means that each user has up to 3 candidate satellites except the serving satellite. Five user terminals are set up in Beijing with the locations following a uniform distribution. We use STK software to simulate the scene and obtain the geographical coordinates of each user. And STK is used to simulate LEO satellite constellation to obtain satellite operation data. Figure 10 compares the performance of four handover strategies in terms of handover failure rate. RST represents the traditional handover strategy based on the remaining service time (RST), which takes the maximum remaining service time as the selection criteria for selecting optimal candidate satellites, and handover is activated when the current serving satellite has no remaining service time. NIC is a traditional handover strategy based on the number of remaining idle channels (NIC), which takes the maximum number of remaining idle channels as the selection criteria for selecting candidate satellites, and handover is activated when there is no remaining service time. MAF is a multi-attribute fusion (MAF) decision based on the TOPSIS evaluation strategy. The strategy considers the remaining service time and the number of idle channels to select the optimal candidate satellite, and handover is activated when there is no remaining service time. IMF is the handover strategy of Intelligent multi-attributes fusion (IMF) decisions based on the DRL, which is proposed in this paper. It can be seen from Figure 10 that the handover failure rate increase with the raise of caching occupancy. Among the strategies, the RST strategy has the highest handover failure rate because it does not consider the remaining channel resources and the remaining caching capacity. Moreover, the growth trends of the handover failure rate of RST, NIC, and MAF are significantly improved when the caching occupancy is higher than 50%. When the caching occupancy is 90%, the handover failure rate is close to 100%. When the caching occupancy is 90%, the handover failure rate of IMF is close to 20%, which shows its performance gain over the referred strategies. Therefore, the proposed IMF handover strategy has the best performance with high caching occupancy. Moreover, the performance of these strategies on call blocking rate is also compared. Here, the call blocking rate is defined as:  
\[P_{block}=\frac{\sum\limits_{slot=1}^{T}\frac{N_{block}}{N_{new}}}{T}. \tag{21}\]  
Here, \(N_{new}\) new coming users arrive in the satellite coverage area and send an access request to the satellite. However, because the satellite does not have enough remaining channel resources for serving all the new coming users, \(N_{block}\) new coming users' access requests are rejected. In this paper, we consider the average call blocking rate in one hour under a high load rate (95% channel occupancy). The call blocking rate can reflect the flex  
Figure 9: Comparison of reward values under different learning rates. ibility of the handover algorithm and the QoS of users in the coverage area. As shown in Figure 11, the call blocking rate of every handover strategy is increasing with the rise of user arrival rate. Among them, the new call blocking rate of RST is the highest because the channel state is not considered. The call blocking rate of the NIC is lower than that of the RST strategy. The MAF strategy considers the remaining service time and the number of idle channels, but the blocking rate is still high because it cannot flexibly adjust the connections of connected users. The IMF strategy can not only consider multiple factors but also flexibly configure the connected user link. If necessary, the connected user link can be reset to the other satellites with the idle channel resources, and it can greatly reduce the call blocking rate.