A UAV traffic prediction considering AP connection errors and UAV altitude

抄録

We propose a traffic prediction method for UAV networks considering connection errors to access points (APs), and demonstrate its effectiveness by calculating the average throughput. In real networks, the performance of devices that serve as APs varies, which may lead to a concentration of loads on high-performance APs. In addition, UAV networks are at risk of communication disconnections and connection errors because UAVs have different altitudes compared to ground-based networks. In this paper, we focus on the possibility that the overall system throughput may change as a result of accidents such as path changes due to the influence of wind, which cause the connection destination to shift to a lower-performance AP, by distributing the load. We use the stochastic evolutionary game theory to analytically solve the changes in throughput for each connection error probability. Moreover, we analyze the characteristic of UAV network with error probability. We also considered the case where there is a difference in altitude between the UAV and the AP, and measured the change in throughput with altitude. We also consider the case where the difference in altitude between the UAV and the AP was tied to the connection error probability.