# Performance Analysis of Downlink 5G Networks in Realistic Environments
## 6 Simulation Results with Discussion
Typically, loss probability is more harmful to performance than blocking probability because, in loss probability, the call is blocked when it is in progress. However, a user is usually blocked or not admitted to the system when the admission conditions are not satisfied based on the applied call admission control algorithm. For example, in this case, the bit rate of the user is less than the threshold value of the minimum bit rate required for cell admission. Fortunately, as shown in Figure 25, good results were obtained for the loss probability compared to the blocking probability values shown in Figure 6:7 For example, the maximum blocking rate shown in Figure 23 at a higher load of 230 Mbit/s is 0.00055 compared to 0.000022 for the loss probability at the same rate. The cell utilization is shown in Figure 6:8 In this figure, one can notice that the utilization of the cell is increased with the increased load, reaching around 85% at a high load of 230 Mbit/s. This result indicates that the cell performance is good, and the call admission control algorithm works well in terms of distrusting the load among users in the cell. In addition, this performance is confirmed by observing Figure 27, where a good throughput value is achieved. Figure 6:9 Aggregate average bit rate for web browsing across zones. Figure 8:0 Cell blocking probability. Figure 8:1 Cell delay. Figure 8:2 Cell average bit rate. Figure 8:3 Cell throughput. Figure 8:4 Cell utilization. In Figures 28-36, the performance of the cell with voice and data services and the impact of mobility on the network performance are outlined. Furthermore, two scenarios are considered in the analysis. In the first scenario, the proportion of data services in the network is increased. As data require more bandwidth than voice, this should affect the performance of the network. In the second scenario, the proportion of mobiles moving at high speed is increased. This parameter should also affect performance. Looking at Figures 28-30, one can notice that the handover dropping probability values (Figure 29) are better than the blocking probability values (Figure 28) at different traffic levels and under various mobility conditions with better performance for voice calls since data utilize more bandwidth than voice. In real life, dropping the call while being in progress is more annoying to the end user than blocking the new call. This effect is reflected in the GoS values given in Figure 8:5 Two additional scenarios are considered in this analysis:  
(A) The impact of increasing the proportion of data services on the performance (Figures 31-33). In this scenario, the arrival density of data services is considered as 0.60 instead of 0.30. The average blocking probability is shown in Figure 8:6 It can be seen from this figure that the blocking probability values at different traffic intensities are higher than the handover-dropping probability values given in Figure 8:7 Due to this behavior, these results are reflected in the GoS values in Figure 33 because the GoS is a combination of the weighted sum of both the blocking and dropping probabilities. This status can be explained as follows. The proposed scenario is very realistic since the number of data services is nowadays expected to be more than the number of voice services as more people are using the internet. Of course, doubling the proportion of data services will have a major impact on performance. Regardless of the performance degradation, the CACA was able to stabilize the status by keeping the dropping probability values at lower rates. (B) The impact of more mobiles are moving with high speed (Figures 34-36). In this scenario, the probability of having 40% high-speed mobiles in the network rather than 10% is considered. In this regard, in Figure 34 for the blocking probability, Figure 35 for the handover dropping probability, and Figure 36 for the GoS, it can be noticed that due to this increase, the overall performance of the network degrades.