# High Throughput Data Relay in UAV Wireless Networks
## 5 Numerical Results  
In this paper, the main metric to assess the system is the average data rate among all the victims which is expressed in units of bits/s/Hz. With a higher average data rate, more throughput can be achieved for the victims. Additionally, the victim bandwidth scheduling and the UAV optimal flight trajectory are also metrics for evaluating the system performance. We consider a system with \(N=4\) victims that are located within an area of size \(800\times 800\) m\({}^{2}\) as illustrated in Figure 2. The UAV is assumed to fly at a fixed altitude of \(H=100\) m. The receiver noise power is assumed to be \(\sigma^{2}=-110\) dBm. The channel power gain at the reference distance of unit length is set to \(\beta_{0}=-50\) dB. The transmit power for the victim is set to \(P=0.1\) W and the maximum flight speed of the UAV is set to \(V_{\max}=50\) m/s [20]. The elemental time slot is set to be \(\delta_{t}=0.5\) s [18]. The threshold to control the iteration of the solution algorithm is set as \(th=10^{-2}\). In this section, we compare the DS scheme with non-DS schemes comprising fair bandwidth allocation and bandwidth contention mechanisms. It should be noted that the bandwidth contention mechanism problem is solved by the BCD-SCA optimization framework. The fair bandwidth allocation  
Figure 2: A disaster scenario topology. mechanism problem is solved assuming fixed bandwidth scheduling. The DS scheme is solved by the BCD-SCA optimization framework, together with the power balance technique. We first list the optimal max-min average data rate for the different schemes for various total period values \(T\) in Table 1. Figure 3 shows the optimal UAV flight trajectories for the different schemes when \(T=60\) s. The DS method has the best performance in terms of average data rate, since the bandwidth is multiplexed by a pair of victims in each time slot. The non-DS bandwidth contention scheme has better throughput performance than the non-DS fair bandwidth allocation scheme as the UAV flies to and hovers above each victim in the bandwidth contention scheme, which brings better channel gain for data transmission. Furthermore, we analyse the theoretical optimal max-min average data rate for the DS scheme under different \(T\), as shown in the last row of Table 1. The theoretical values for the scenario shown in Figure 2 are feasible to calculate. Within time \(T\), the UAV should spend the most time supporting the DS enabled victims, and spend the least time traversing from the initial position to the final position. To be specific, the UAV should traverse at its maximum speed, and for the remaining time hover at two positions, one is the midpoint of line segment victim1-victim2, and the other is the midpoint of line segment victim3-victim4. By letting the UAV hover at the midpoint, it is able to maximize the received signal power at the UAV for the paired DS enabled victims. From a comparison of the results, we can see that the proposed solution is very close to the theoretical values, which shows the correctness and feasibility of our proposed approach. In addition, the proposed technique can be treated as a general method to solve the DS enabled UAV trajectory planning problem. Since the theoretical analysis is not always easy to undertake, due to the complex network topology, the proposed approach provides a practical way to get close to the ground true optimal value. Figures 4 and 5 show the bandwidth schedule for each victim in the DS method and non-DS bandwidth contention scheme, respectively. In the DS scheme, victim 1 and victim 2 are supported by the \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \(T=60\) s & \(T=40\) s & \(T=30\) s & \(T=20\) s \\ \hline non-DS bandwidth contention scheme & 10.40 & 9.99 & 9.63 & 9.12 \\ non-DS fair bandwidth allocation scheme & 9.80 & 9.78 & 9.76 & 9.71 \\ DS method & 14.65 & 14.64 & 14.62 & 14.58 \\ DS method (theoretical analysis) & 14.70 & 14.67 & 14.63 & 14.58 \\ \hline \hline \end{tabular}
\end{table}