An Energy-Effective and QoS-Guaranteed Transmission Scheme in UAV-Assisted Heterogeneous Network

In this article, we consider a single unmanned aerial vehicle (UAV)-assisted heterogeneous network in a disaster area, which includes a UAV, ground cellular users, and ground sensor users. The cellular data and sensing data are transmitted to UAVs by cellular users and sensor users, due to the outage of the ground wireless network caused by the disaster. In this scenario, we aim to minimize the energy consumption of all the users, to extend their communication time and facilitate rescue. At the same time, cellular users and sensor users have different rate requirements, hence the quality of service (QoS) of the users should be guaranteed. To solve these challenges, we propose an energy-effective relay selection and resource-allocation algorithm. First, to solve the problem of insufficient coverage of the single UAV network, we propose to perform multi-hop transmission for the users outside the UAV's coverage by selecting suitable relays in an energy-effective manner. Second, for the cellular users and sensor users inside the coverage of the UAV but with different QoS requirements, we design a non-orthogonal multiple access (NOMA)-based transmission scheme to improve spectrum efficiency. Deep reinforcement learning is exploited to dynamically adjust the power level and allocated sub-bands for inside users to reduce energy consumption and improve QoS satisfaction. The simulation results show that the proposed NOMA transmission scheme can achieve 9-17% and 15-32% performance gain on the reduction of transmit power and the improvement of QoS satisfaction, respectively, compared with state-of-the-art NOMA transmission schemes and orthogonal multiple access scheme.