An intelligent resource dynamic allocation method for UAV wireless mobile network which supports QoS Abstract   The development of Unmanned Aerial Vehicle (UAV) business requires that the wireless mobile network can provide the highest possible data rate with limited wireless resources and harsh channel environment, while ensuring the requirements of different quality of service (QoS). The present algorithm only considers one or two spatial sub channels with the maximum eigenvalue, and does not consider how to satisfy multiple requirements with limited resources, nor does it consider the problem of admission control. In order to solve the above problems, this paper proposes an intelligent resource dynamic allocation method based on QoS. In this paper, resources are managed effectively through resource reservation mechanism and selective QoS adjustment mechanism. Then, all nonzero eigenvalue space sub channels are used for data transmission to maximize channel capacity under the condition that the total transmission power is limited and user QoS requirements are met. The simulation results show that the algorithm can effectively improve the throughput of the system by making full use of multiuser diversity on the basis of satisfying the QoS requirements of users.

EnergyEfficient UAVAssisted Communication with Spectrum optimization In traditional ground cellular systems, ground terminals (GTs) in marginal areas are often faced with performance bottlenecks due to they are too far from the macro base station (MBS). For some temporary and unexpected communication service requirements, it is uneconomical to deploy femtocell access points (FAPs) on the edge of cell. In this paper, we investigate a cellular system that utilizes a unmanned aerial vehicles (UAVs) with base station module unit as an airborne mobile base station to provide communication channel for the celledge users offloaded by the MBS. Compared with FAPs, UAV is cheaper and flexible which can provide better communication quality for the celledge GTs with better channel condition. Based on the theoretical model, we proposed plausible optimal algorithm to maximize the energyefficiency (EE) of the UAV by jointly optimizing the spectrum allocation, flying speed and user partition between the UAV and MBS. Numerical results indicate that our design could achieve relatively higher energyefficiency by exploiting optimal flight strategy and spectrum allocation strategy.