# UAV Based Relay for Wireless Sensor Networks in 5G Systems
## 5 Research Direction and Conclusions  
We have introduced the LU algorithm to determine the position of a UAV in WSN. However, to simplify the paper, we use an oversimplified model to reveal the relationship between the three-dimensional positioning of the UAV and the system energy consumption, where the three-dimensional space has been considered in only one dimension. In the future, we should further extend the work into more practical scenarios. In Figure 7, we give several scenarios based on the UAV in WSN. For the Scenario \(A\) in Figure 7, when multiple concentrators and UAV exist in system, the position of the UAV will largely affect the performance of WSN. Unlike the case in Figure 2,  
Figure 5: The impact of \(B_{U}\) on system power consumption (how to cut down the power consumed in system by increasing wireless bandwidth of UAV (Hz)). Figure 6: The impact of \(B_{U}\) on \(M=\frac{\gamma}{T}\) (how to place the UAV under different configurations of \(B_{U}\)). when multiple UAVs are considered the optimal position of the UAV cannot be directly obtained by the LU algorithm. To network the relays in WSN and determine the number of relay stages in WSN will be our future work. At the bottom of Figure 7, we map out the second scenario for a UAV based relay. In this case, to avoid the obstacles blocking the wireless transmission in sight distance, the UAV can act as the relay between the source and the destination for the signal transmitting. Figure 7: Scenarios of UAV based relay in WSN. On the other hand, the flightpath selection algorithm of UAV will be proposed in our future work to achieve the best path for data collection. As shown in Figure 8, different paths of UAV will determine the different wireless channel gains employed to collect the concentrator data. Unlike the model in this paper, UAV in Figure 8 can fly in three-dimensional space. The optimal flightpath can be determined by machine learning, etc., which will be left for our future work. Moreover, several issues should be further studied in future work to increase practicality. We observe the issues as follows:  
1. When frequency subchannels, fast fading, and slow fading are considered, the optimal position for a specific UAV differs across the frequency of subchannels. How to determine the optimal position will be an intractable problem. 2. Considering the power consumption of UAV flight, how does the optimal position of a UAV change. 3. How to determine the optimal flightpath. This is a key issue for the UAV based relay due to the moving feature of a UAV. 4. How to achieve the tradeoff between the number of UAV and the performance of the WSN. This should be appropriately determined by an optimization tool, such as geometric programming optimization, etc. 5. A caching [19; 20; 21] based UAV relay will be investigated where queuing theory should be employed to analyze the performance of the WSN system. In conclusion, this paper aims to propose the UAV based relay in WSN to determine the optimal position of UAV based on the wireless environment for minimizing the system's power consumption. Such an architecture can effectively make up for the disadvantage of the small transmitting power of the wireless devices in WSN. As \(B_{U}\) increases, a UAV can approach the concentrator (i.e., \(M\) decreases) to decrease the transmitting power of the concentrator. To determine the optimal staying position of the UAV, we have also proposed a simple scenario and the corresponding LU algorithm based on the revealed philosophy of the UAV position to obtain the optimal position minimizing the system power consumption. We have verified the effectiveness of the proposed algorithms via extended simulations. Figure 8: Flight path selection of UAV. **Author Contributions:** Conceptualization, S.F. ; Methodology, S.F. and Z.S. ; Software, S.F. and X.J. ; Validation, S.F. and L.Z. ; Writing-Original Draft Preparation, S.F. ; Writing-Review & Editing, S.F. and L.Z. ; Visualization, S.F. and X.J. ; Project Administration, S.F. and X.J. ; Funding Acquisition, S.F.