inis 21(27): e2

Research Article

Performance Analysis for RF Energy Harvesting Mobile Edge Computing Networks with SIMO/MISO-NOMA Schemes

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  • @ARTICLE{10.4108/eai.28-4-2021.169425,
        author={Dac-Binh Ha and Van-Truong Truong and Yoonill Lee},
        title={Performance Analysis for RF Energy Harvesting Mobile Edge Computing Networks with SIMO/MISO-NOMA Schemes},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={8},
        number={27},
        publisher={EAI},
        journal_a={INIS},
        year={2021},
        month={4},
        keywords={radio frequency energy harvesting, mobile edge computing, non-orthogonal multiple access, Nakagami-m fading, multi-antenna},
        doi={10.4108/eai.28-4-2021.169425}
    }
    
  • Dac-Binh Ha
    Van-Truong Truong
    Yoonill Lee
    Year: 2021
    Performance Analysis for RF Energy Harvesting Mobile Edge Computing Networks with SIMO/MISO-NOMA Schemes
    INIS
    EAI
    DOI: 10.4108/eai.28-4-2021.169425
Dac-Binh Ha1,*, Van-Truong Truong1, Yoonill Lee2
  • 1: Faculty of Electrical-Electronic Engineering, Duy Tan University, Da Nang, 550000, Vietnam and the Institute of Research and Development, Duy Tan University, Da Nang
  • 2: Faculty of Electrical Engineering Technology at the College of Lake County, Grayslake, IL, USA
*Contact email: hadacbinh@duytan.edu.vn

Abstract

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 closed-form 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.