Fair Energy-Efficient Resource Optimization for Green Multi-NOMA-UAV Assisted Internet of Things

Owing to the advantages of better air-ground channel and higher flexibility, unmanned aerial vehicle (UAV) has been widely applied in the field of Internet of Things (IoT) to increase the communication coverage. However, the UAV with limited energy is facing severe energy shortage when serving more and more IoT devices. In this paper, we propose a non-orthogonal multiple access (NOMA) based green multi-UAV assisted IoT system to increase user capacity while improving the energy utilization of each UAV. Considering the limited energy budget of each UAV, we formulate a fair energy-efficient resource optimization problem under the constraints of maximum transmit power of each UAV, minimum communication rate requirement of each user and UAV mobility. By alternately optimizing the communication scheduling, transmit power allocation and UAV trajectory with the Dinkelbach method and the successive convex approximation (SCA), the energy-efficient fairness can be achieved between the UAVs by maximizing the minimum energy efficiency of the UAVs. The simulation results indicate the fair energy efficiency between the UAVs can be obtained through the alternative resource optimization, and the proposed multi-NOMA-UAV assisted IoT can get higher energy efficiency than the traditional orthogonal multiple access (OMA)-UAV assisted IoT.

Automated summary

In this paper, a green multi-UAV assisted IoT system based on non-orthogonal multiple access (NOMA) is proposed to improve energy efficiency and fairness among UAVs. By optimizing communication scheduling, transmit power allocation, and UAV trajectory, the minimum energy efficiency of the UAVs is maximized.