Adaptive Decoding Mechanisms for UAV-enabled Double-Uplink Coordinated NOMA

In this paper, we propose a novel adaptive decoding mechanism (ADM) for the unmanned aerial vehicle (UAV)-enabled uplink (UL) non-orthogonal multiple access (NOMA) communications. Specifically, considering harsh UAV environment, where ground-to-ground links are regularly unavailable, proposed ADM overcomes challenging problem of conventional UL-NOMA systems whose performance is sensitive to transmitter's statistical channel state information and receiver's order. To evaluate ADM, derive closed-form expressions system outage probability (OP) throughput. analysis section, provide practical air-to-ground ground-to-air channels, while taking into account implementation imperfect successive interference cancellation (SIC) in UL-NOMA. Moreover, obtained expression can be adopted characterize OP various under Mixture Gamma (MG) distribution-based fading channels. Next, sub-optimal Gradient Descent-based algorithm obtain power allocation coefficients that result maximum throughput with respect each location on UAV's trajectory. determine significance nonstationary environments, consider ground users move according Random Waypoint Mobility (RWM) Reference Point Group (RPGM) models, respectively. Accurate formulas distance distributions also provided. Numerical solutions demonstrate ADM-enhanced NOMA not only outperforms Orthogonal Multiple Access (OMA), but improves UAV-enabled even mobile environments.