User Fairness Optimization for Multi-UAV-Aided NOMA Networks: A Location-Aware Perspective

Abstract

In the blind areas of current fifth generation (5G) networks, e.g. the remote areas, unmanned aerial vehicles (UAVs) can be used to provide on-demand connectivity. To efficiently serve the sparsely distributed users in these areas, non-orthogonal multiple access (NOMA) could be adopted to exploit the user distinguish ability in the power domain. In this paper, we consider a NOMA-based multi-UAV-aided network, where a swarm of coordinated UAVs transmit messages to unevenly distributed users through a virtual multiple-input-multiple-output (MIMO) channel. We formulate a power allocation problem to maximize the minimum user rate to assure fairness in the transmission. Different from existing studies, we use only the large-scale channel state information (CSI) in the transmission design, which characterizes the basic channel feature, and can be obtained using the location information of UAVs/users. By leveraging the random matrix theory and successive convex optimization tools, we propose an iterative algorithm to solve the problem after a series of problem transformation. Simulation results show that the proposed power allocation scheme outperforms existing methods, which shows the potential of multi-UAV-aided NOMA communications for coverage enhancement in remote areas.