Design and Optimization of a UAV-Enabled Non-Orthogonal Multiple Access Edge Computing IoT System.

Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) in IoT systems has recently gained prominence as a solution to accommodate the low latency and high energy efficiency needs of emerging and developing 5G-and-beyond IoT applications. Given the limited spectrum available, non-orthogonal multiple access (NOMA) communication scheme provides a spectral- and power-efficient task offloading means. In this work, a novel framework is proposed for a multiple-UAV-enabled MEC IoT system incorporating uplink NOMA. The goal is to maximize the sum bits offloaded from all the IoT devices (IoTDs) in a finite service period. This is achieved through joint optimization of the associations between the IoTDs and the UAVs, the IoTD transmit powers, as well as the UAV trajectories, given UAV and IoTD energy budgets and quality-of-service (QoS) criteria. Towards that end, a specialized penalty block coordinate descent (P-BCD) algorithm is proposed to decompose the original problem into 4 subproblems that are solved alternately and iteratively. By direct comparison with several benchmark schemes including orthogonal multiple access (OMA), our proposed scheme displays performance enhancement in terms of sum bits offloaded and energy expenditure. Finally, a performance comparison is carried out for the proposed scheme with different number of employed UAVs to find the most cost-effective number of UAVs to deploy.