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%.

在紧急情况下，无人飞行器（UAV）可以迅速部署为空中基站，为用户提供通信服务。室外传输模型和室外室内传输模型无法规范化，当无人机为室内用户和室外用户服务时，很难建立有效的混合传输模型。我们提出了一种“室内-室外-迭代优化”（IOI）覆盖方案，该方案不需要建立混合传输模型，即先覆盖室内用户，然后覆盖室外用户，最后覆盖迭代优化。当户外用户的位置信息未知时，无法准确计算出用户所需的带宽和功率。为了获得户外用户的位置信息，我们提出了一种通过使用用户密度来估计户外用户分布（MEUD）的方法。我们进一步估计了所有用户的发射功率，大大减少了计算量。仿真结果表明，用户密度越大，估计值越接近准确值。根据用户分布，我们提出了一种基于3D位置，功率和带宽分配的方案，该方案可以最大化室内用户和室外用户的覆盖范围，并确保所有用户的公平性。根据剩余资源与户外用户所需资源之间的大小关系，我们将情况分为三种情况。在三种情况下讨论了该方案的可行性，并分别给出了具体算法。最后，我们给出了基于三种情况的综合算法。