A Unified Framework for HS-UAV NOMA Networks: Performance Analysis and Location Optimization

In this paper, we propose a unified framework for hybrid satellite/unmanned aerial vehicle (HS-UAV) terrestrial non-orthogonal multiple access (NOMA) networks, where satellite aims to communicate with ground users with the aid of a decode-forward (DF) UAV relay by using NOMA protocol. All users are randomly deployed to follow a homogeneous Poisson point process (PPP), which is modeled by the stochastic geometry approach. To reap the benefits of satellite and UAV, the links of both satellite-to-UAV and UAV-to-ground user are assumed to experience Rician fading. More practically, we assume that perfect channel state information (CSI) is infeasible at the receiver, as well as the distance-determined path-loss. To characterize the performance of the proposed framework, we derive analytical approximate closed-form expressions of the outage probability (OP) for the far user and the near user under the condition of imperfect CSI. Also, the system throughput under delay-limited transmission mode is evaluated and discussed. In order to obtain more insights, the asymptotic behavior is explored in the high signal-to-noise ratio (SNR) region and the diversity orders are obtained and discussed. To further improve the system performance, based on the derived approximations, we optimize the location of the UAV to maximize the sum rate by minimizing the average distance between the UAV and users. The simulated numerical results show that: <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>) there are error floors for the far and the near users due to the channel estimation error; <inline-formula> <tex-math notation="LaTeX">$ii$ </tex-math></inline-formula>) the outage probability decreases as the Rician factor <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> increasing, and <inline-formula> <tex-math notation="LaTeX">$iii$ </tex-math></inline-formula>) the outage performance and system throughput performance can be further improved considerably by carefully selecting the location of the UAV.