# NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations
## 4 Proposed Method
### Fractional Frequency Reuse to UAV Network  
The frequency division method in the previous section narrows the bandwidth for all users, which improves throughput for users who originally suffer from high interference. On the other hand, the scheme reluctantly reduces throughput for users who originally experience low interference due to the spectrum division process. Therefore, it is necessary to investigate a novel frequency division method to only take care of the interference to users who originally suffer high interference while still guaranteeing sufficient bandwidth to original users suffering low interference, resulting in the improvement of the overall spectrum usage efficiency.  
Figure 4: Example of Algorithm 1[19].  
To solve this problem, we consider introducing Fractional Frequency Reuse (FFR), which has been studied in terrestrial cellular networks, to the UAV network. Figure 4(a) shows the outline of FFR. As shown, the area far from the base station in Cell 1, fI, which does not interfere with other base stations, is used because interference with other base stations is a concern. On the other hand, in the area around the base station where the interference with other base stations is small, all the bandwidths in use are used. Thus, in FFR, users near a base station, i.e., users who experience less interference from other base stations, are prevented from losing frequency efficiency by repeatedly using the same bandwidth as other base stations. In this way, users near the base station can be guaranteed a wider bandwidth than the case where the frequency for each base station is divided equally.  
We consider the application of this technique to UAV networks. In a UAV network, as described in the previous section, the number and size of overlapping coverage varies depending on the dynamic variation of the user distribution and the corresponding changes of UAV placements. Furthermore, users with little interference are not necessarily located close to the servicing base station similar to the situation on the ground. Therefore, we propose rules that can be adapted to various situations, as explained below.  
Figure 4(b) shows a situation where three cells overlap. In this method, the bandwidth is set by the overlap of the coverage, not by the distance to the base station. As shown in Figure 4(b), Cell 1 uses the entire bandwidth in areas where there is no overlap in coverage, i.e., areas with little interference. In addition, fI' is used in areas where the coverage overlaps, i.e., where the interference is high. Users in overlapping areas are served by the closest UAV. By using this rule, it is possible to clarify which UAV will provide the data even if the coverage is complicated. The details of this algorithm are shown in Algorithm 2. Algorithm 2 has much in common with Algorithm 1, and both are aimed at efficient bandwidth partitioning. However, Algorithm 2 outputs different allocation results due to the existence of Process 8 (assignment of bandwidth to coverage overlapped UEs) and Process 10.  
Figure 5: FFR overview.  
In the above algorithm, \(\{n_{\bar{k}}\}\) denotes the set of the number of users accommodated in the interference-limited area by the UAVs overlapping the coverage of the \(k\)-th UAV. It should be noted in Process 8 that if Algorithm 1 employs \(N_{\bar{k}}^{l}\), i.e., the number of all accommodated users by an overlapping UAV for frequency splitting, Algorithm 2 uses only \(n_{\bar{k}}\), i.e., the number of users in the interference-limited overlapped area for frequency splitting in only the outer area that might suffer from inter-cell interference.