UAV-enabled IoT Systems: NOMA or OMA?
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This paper investigates unmanned aerial vehicle (UAV) enabled Internet-of-Things (IoT) systems with a couple of multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple IoT devices. Our goal is to maximize the minimum UAV data collection throughput from IoT devices for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) schemes, subject to the energy budgets of both the UAV and IoT devices. 1) For the OMA scheme, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblems are alternatively solved by applying successive convex approximation (SCA) technique. 2) For the NOMA scheme, we first handle subproblems with fixed decoding order with SCA technique. Then, we design a penalty-based algorithm to solve the decoding order design subproblem. Thus, we propose another AO-based algorithm to derive a locally optimal solution for the NOMA scheme. Numerical results illustrate that: 1) the proposed algorithms improve the max-min throughput performance compared with other benchmark schemes; 2) the NOMA scheme always achieves no worse performance than that of the OMA scheme.
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