Energy-Efficiency Optimization for Multiple Access in NOMA-Enabled Space–Air–Ground Networks

Abstract

Due to the flexible deployment of unmanned aerial vehicles (UAVs) and the wide-area coverage of satellites, the space-air-ground (SAG) communication network can provide flexible and pervasive connectivity, especially in remote areas. In this work, we investigate the uplink transmission in a SAG network, where the non-orthogonal multiple access mechanism is adopted at the UAVs to enhance the number of access from ground user equipments (UEs) and a low earth orbit satellite offers the wireless backhaul for UAVs. In particular, the energy efficiency (EE) of the considered network is maximized by optimizing the user association (UA), the power allocation (PA), and the UAV 3D trajectory jointly with the consideration of the movement of the satellite. To tackle the formulated problem, by leveraging the block coordinate descent (BCD) method, we develop a joint UA, PA, and UAV trajectory (namely, JUPT) optimization algorithm, i.e., the original problem is decomposed into three subproblems, and the subproblems are solved iteratively until convergence. Specifically, we propose to include the virtual UEs in the system and develop a low-complexity matching algorithm to effectively solve the UA problem. A successive convex approximation (SCA)-based Dinkelbach algorithm is then adopted to address the PA problem. Later, with the introduction of the auxiliary variables, the UAV 3D trajectory subproblem is iteratively solved by the SCA method. Our numerical results demonstrate the superiority of the proposed JUPT algorithm, which obtains significantly higher EE compared to the benchmark schemes. Moreover, the rapid convergence of the JUPT algorithm is verified.