# User QoS-Based Optimized Handover Algorithm for Wireless Networks
## 3 User QoS-Based Optimized Handover Algorithm
### Optimized Handover Algorithm with QoS Requirements (OHAQR)  
The proposed handover algorithm based on the user's high QoS requirements is shown in Algorithm 2; the algorithm will perform the best handover according to the settings of the user's service throughput and PLR requirement, and the trade-off results obtained after individual weighting of decisions are used as indicators for evaluation. The QoS metrics mentioned above have high priority in handover decisions. Combined with the \"optimized handover algorithm\" proposed in this paper, if the QoS-based handover conditions are satisfied, even if the three handover conditions mentioned in the optimized handover algorithm that need to be satisfied at the same time are not met, the handover procedure will still be triggered. The trigger conditions for the handover are as follows. If the user enables the setting of high QoS requirements, the weight of handover decision parameters with high QoS requirements can also be set according to the attributes and requirements of the application used by the user. Through a weight-based handover decision such as that in [16], we designed a trade-off strategy between throughput and PLR based on user settings for different application scenarios. In the case of maintaining high throughput, if the current throughput (\(TP^{C}\)) capacity between the UE and the currently connected AP is lower than the \"minimum throughput requirement threshold (\(T^{QoS}\))\" minus the \"minimum throughput requirement HM (\(HM^{QoS}\))\", this will immediately trigger the handover procedure (as shown in Figure 3, and line 11 in Algorithm 2). At the same time, if a PLR handover decision parameter with a lower weight is set, the handover algorithm will also consider the PLR performance of the service network. If the low PLR exceeds the tolerable level according to the set weight, although the throughput performance is still within an acceptable range, the low PLR performance will further affect the user's network experience. At this time, the handover procedure is also triggered to immediately alleviate the low PLR problem, thereby improving the user's QoS. On the contrary, if the PLR is a network performance indicator that users attach more importance to, if the PLR is lower than the threshold set by the user, it will immediately hand over, and if the weight of throughput of the handover decision has been set, the throughput performance will also be considered, and the best execution timing for handover is determined based on its weight to ensure that the user can always have sufficient QoS during the use of the network. The Q-score curve in Figure 3 is the QoS score variation of each data sampling point obtained after the trade-off calculation of Equation (2). In addition to considering throughput and PLR, the immediacy of the application is also considered. If the AP currently being used by the UE requires a low-latency network environment, the system will consider the immediacy when making a handover decision to provide a low-latency network experience at all times. In addition, signal interference between APs was found after experiments and, although it did not seriously affect the network experience, we still used the number of nearby APs that could be searched by the UE as the number of interference signal sources. If there are many nearby interference sources, the overall QoS score will be lowered. Based on the above parameters, the values, in the range of 0-1, obtained by the normalization algorithm are multiplied by the individual weights of each parameter. After these values are added up, the result obtained is used to define the Q-handover score of handover decisions. When the Q-handover score is lower than the \"user-defined QoS threshold (\(T^{\text{QoS}}\))\", the handover procedure will be triggered.