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In this paper, we study an RF energy harvesting mobile edge computing network based on a SIMO/MISO system and NOMA schemes over Nakagami-m fading. Specifically, a multi-antenna user harvests RF energy from a power station by using a selection combining/maximal ratio combining scheme and offload its tasks to two MEC servers through downlink NOMA by employing transmit antenna selection/maximal ratio transmission scheme. Accordingly, we investigate the performance of six schemes, namely SC-TAS1, SC-TAS1, MRC-TAS1, MRC-TAS2, SC-MRT, and MRC-MRT, for this considered system. To evaluate the performance, exact closedform expressions of successful computation probability are derived. We further propose the optimal algorithm to find the best parameter sets to achieve the best performance. Moreover, the impacts of the network parameters on the system performance for these schemes are investigated. Finally, the simulation results are also provided to verify the accuracy of our analysis.

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This paper studies unmanned aerial vehicle (UAV)-aided nonorthogonal multiple access (NOMA)-based mobile-edge computing (MEC) in Internet of Things (IoT) systems in which the UAV acts as relay (UR). Specifically, we consider a scenario with two cluster IoT devices (IDs) (i.e., a high-priority cluster IA and a low-priority cluster IB) with limited resources, so these IDs cannot compute their tasks and must offload them to a base station (BS) through UR. We propose a protocol named time switching -radio frequency (RF) energy harvesting (EH) UR NOMA (REUN) (TS-REUN), which is divided into 5 phases. By applying the TS-REUN protocol, the IDs in two clusters and UR harvest RF energy from the broadcasting signal of the power beacons (PB). Then, the IDs offload their tasks to the MEC server located at the BS. After server processing, the IDs receive the calculation results from the BS via UR. The effects of both imperfect channel state information (ICSI) and imperfect successive interference cancellation (ISIC) on the REUN-based MEC (REUN-MEC) are taken into account. To evaluate the performance of the system, we derive closed-form expressions for the successful computation probability (SCP) and energy consumption probability (ECP) under the Nakagami-m fading channel. Moreover, we propose an optimization problem formulation that aims to maximize SCP by optimizing the position and height of UR and the time switching ratio (TSR). The problem is addressed by employing an algorithm based on particle swarm optimization (PSO). In addition, the Monte Carlo simulation results are presented to confirm the accuracy of our analysis based on system performance simulations with various system parameters, such as the number of antennas at the BS, the number of IDs in each cluster, TSR, and the position and height of UR.INDEX TERMS Internet of Things, unmanned aerial vehicles, energy harvesting, nonorthogonal multiple access, mobile-edge computing.

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