# A Fuzzy-Logic-Based Load Balancing Scheme for a Satellite-Terrestrial Integrated Network
## 3 Results
### Performance of the Fuzzy-Logic-Based Offloading Algorithm  
In order to evaluate the performance of the offloading algorithm, a special user dropping method was used. Two of the cells with more users were dropped to emulate overloading. Additionally, users accessed cells based on the basic algorithm, BCA. The proposed FL-OL is compared with AMMO. Whenever overloading occurred, the two offloading algorithms were utilized, respectively, to offload users to other available cells. After a period of time, the cell could overload again due to the dynamic changes of the environment. The time interval of the first or second overload time is called the next overload interval. Although the current signal reception quality of some users is poor, they may be moving toward the current serving cell and away from adjacent cells. Such users are likely to be selected if the offloaded users are selected only according to RSRP, which may bring a heavy load to the adjacent cell. The rate requirement is also an important factor. Low rate users have little impact on the overloading and should have a lower priority for being offloaded. Unlike AMMO, FL-OL takes the above factors into account by introducing FEM and should be able to prolong the time with a balanced load for the system.  
Figure 5: The overload ratio with different algorithms.  
Figure 6: The satisfied ratio with different algorithms.  
Figure 7 shows the next overload interval for the two algorithms and different numbers of users. The next overload interval of both algorithms decreases with the increase in users due to limited frequency resources. FL-OL makes the next overload interval longer by about 17%. It proves our inference that by considering future changes, FL-OL prolongs the time that the system maintains load balance. In the long run, it will reduce the number of times of calling the offloading algorithm and the number of times of handover.  
With an increase in users and limited TN frequency resources, it is more difficult to balance load when only relying on TN cells. The number of users served by each satellite is increasing. However, there are always less users offloaded to NTN with the proposed FL-OL due to it making more effective use of the TN's resources. As shown in Figure 8, FL-OL reduces users affected by the delay of long-distance transmission of satellite-user link by up to 14% compared with the existing algorithm.  
Furthermore, to verify the effectiveness of the proposed algorithm, Figure 9 shows the average data rate before and after offloading. With an increase in users, the limited  
Figure 8: Number of users served by a satellite with different algorithms.  
Figure 7: Next overload interval with different algorithms.  
resources of the overloaded cell struggle more difficult to meet users' rate requirements so that the average rate decreases significantly. After performing offloading, the average rates increased by 10% to 70% with different user numbers, and users basically met their target data rates. The results show that overloading will significantly affect QoS, and once again verifies that the scheme of reducing the overloading through active load balancing in this paper is meaningful.