# NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations
## 5 Simulation Results
Moreover, as explained in Section 3.2.2, since this paper assumes a TDMA communication method when a UAV needs to serve multiple users, the more users that are accommodated by a UAV, the less the data rate each user has associated with this UAV experience, as the overall communication resources in the time domain need to be shared equally for each accommodated user of the cell. The edge-prior method [7] that we are comparing is an existing method and is one that ensures that the number of users accommodated by each UAV is equal, starting from users at the edge of the area. From Figure 7, we can see that by introducing the smallest-circle problem to the K-means method, the offered data rate is improved compared to the existing deployment methods. The edge-prior method results seem to be convex upward (concave downward) twice around 15 Mbps. This is because this research uses a user distribution that is not uniform. We believe that this result is not surprising. Figure 10: Outage 5% data rate for each number of UAVs. Figure 9: The mean data rate for each number of UAVs. can be attributed to the fact that by using this edge-prior method of accommodating a certain number of users, there are two types of users: those who are accommodated by UAVs with small coverage (and high user data rate since these UAVs fly at lower altitude close to the users) and those who are accommodated by UAVs with large coverage (and small user data rate since these UAVs fly at higher altitude to cover sparsely distributed users), yielding these two humps in performance. Figure 7 also reveals the superiority of our method (K-means + smallest circle) since the CDF curve is mostly the right-most scheme compared to the other schemes. In particular, the proposed scheme has better performance than the conventional K-means method at almost all regions of the CDF. This is due to the introduction of the smallest circle mechanism to reduce wasted coverage and also inter-cell interference. Compared to the conventional edge-prior method, the proposed method also has superior performance at almost all regions of the CDF, except for the region around 15 Mbps on the x-axis (or 65% of the CDF on the y-axis) which has almost the same performance as the edge-prior method. We believe the reason behind this phenomenon is due to the existence of UAVs that accommodate more users than these of the edge-prior method, where each UAV was restricted to accommodate the same number of users (since the algorithm in [38] was originally designed for uniform user distribution rather than the non-uniform distribution considered in this paper). Due to the existence of these \"more-user\" UAVs, the average user rates of these cells are slightly reduced due to the TDMA effect applied on users of the same cell. In summary, the trade-off between the reduction of the user rate due to resource sharing in the time domain and the increase of channel capacity owing to the benefit of our proposed UAV placement method explains the phenomenon at the region around 15 Mbps. Based on the proposed deployment method, in the next step, we will check the performance of different frequency division methods to further improve the offered throughput. Figure 8 shows the CDF of the data rate provided by each user for each method of frequency division. For the UAV placement method, the proposed K-means method plus the smallest-circle problem is introduced. From the left bottom side of Figure 8, by dividing the frequency of each UAV, the offered data rate can be improved for users originally suffering high interference (with low data rates). However, the overall offered data rate is significantly reduced because the bandwidth is split even for users originally not suffering many interferences (with high data rates), as seen in the upper right side of the CDF. On the other hand, by using FFR adapted to the UAV network, we were able to increase the offered data rate for users suffering high interference while minimizing the overall loss in the offered data rate.