Research on NOMA decoding methods for UAV-assisted MEC scenarios

In the context of unmanned aerial vehicles-assisted mobile edge computing for emergency communication scenarios, the issue of high system energy consumption arises due to the impact of serial interference cancellation decoding order in non-orthogonal multiple access on users' task completion time and the limitation of uplink task offloading link transmission performance. To address this, a non-orthogonal multiple access UAV-assisted mobile edge computing algorithm based on user priority is proposed. Firstly, a Serial Interference Cancellation decoding order algorithm based on user priority is established. Secondly, by jointly considering computational resource allocation and transmission power, a problem aimed at minimizing the system's weighted total energy consumption is formulated. Finally, due to the non-convex nature of this optimization problem, the successive convex approximation method and quadratic transformation are employed to convert the objective function into a convex optimization problem. Simulation results demonstrate that, compared to the channel gain-based decoding order approach, the user priority-based SIC decoding order access method can more effectively reduce system energy consumption, achieving a reduction of approximately 3.38%.