Energy-Constrained UAV Data Collection Systems: NOMA and OMA

This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect from ground nodes (GNs). Our goal maximize the minimum throughput GNs for both orthogonal (OMA) and non-orthogonal (NOMA) transmission, subject energy budgets at GNs, namely \emph{double limitations}. 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, each subproblem alternately solved applying successive convex approximation (SCA) technique. 2) NOMA, first handle subproblems fixed decoding order using SCA Then, develop penalty-based solve design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving max-min performance compared other benchmark schemes; ii) NOMA yields higher gain than OMA when have sufficient energy.