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Statistical Modeling of Energy Harvesting in Hybrid PLC-WLC Channels

Author

Listed:
  • Victor Fernandes

    (Department of Telecommunications Engineering, Fluminense Federal University, Niterói 24210 240, RJ, Brazil)

  • Thiago F. A. Nogueira

    (Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036 330, MG, Brazil)

  • H. Vincent Poor

    (Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA)

  • Moisés V. Ribeiro

    (Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036 330, MG, Brazil)

Abstract

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.

Suggested Citation

  • Victor Fernandes & Thiago F. A. Nogueira & H. Vincent Poor & Moisés V. Ribeiro, 2021. "Statistical Modeling of Energy Harvesting in Hybrid PLC-WLC Channels," Sustainability, MDPI, vol. 14(1), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2021:i:1:p:442-:d:715700
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    References listed on IDEAS

    as
    1. Ioannis P. Chochliouros & Michail-Alexandros Kourtis & Anastasia S. Spiliopoulou & Pavlos Lazaridis & Zaharias Zaharis & Charilaos Zarakovitis & Anastasios Kourtis, 2021. "Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures," Energies, MDPI, vol. 14(17), pages 1-14, August.
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