A decision-making scheme for UAV maximizes coverage of emergency indoor and outdoor users

Abstract In emergency situations, unmanned aerial vehicle (UAV) can be quickly deployed as air base station to provide users with communication services. The outdoor transmission model and outdoor-indoor transmission model cannot be normalized, and an effective hybrid transmission model is difficult to establish when the UAV serves both indoor users and outdoor users. We propose a ”indoor-outdoor-iterative optimization” (IOI) coverage scheme that does not require the establishment of a hybrid transmission model, that is, covering indoor users first, then outdoor users, and finally iterative optimization. When the outdoor user’s location information is unknown, the user’s required bandwidth and power cannot be accurately calculated. In order to obtain the location information of outdoor users, we propose a method to estimate outdoor user distribution (MEUD) by using user density. We further estimate the transmit power of all users, and greatly reduce the calculation amount. Simulation results show that the greater the user density, the closer the estimated value is to the accurate value. By user’s distribution, we propose a scheme based on 3D location, power and bandwidth allocation, which can maximize the coverage of indoor users and outdoor users and ensure the fairness of all users. According to the size relationship between the remaining resources and the resources required by outdoor users, we divide the situation into three cases. The feasibility of the scheme is discussed in three cases, and specific algorithms are given respectively. Finally, we give a comprehensive algorithm based on three cases. The simulation results show the effectiveness of the algorithm and ensure that the gap in communication rate between users of MEUD is less than 0.5%.