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