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Performance Analysis of Cognitive Femtocell Network with Ambient RF Energy Harvesting

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2018, ruSMART 2018)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11118))

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Abstract

Radio frequency (RF) energy harvesting is a promising technique to collect energy from the concurrent downlink transmissions. This energy after converting it into DC power can power up such devices as cell phones, Wi-Fi networks, etc. In this paper, a model of RF energy harvesting in the cognitive femtocell is presented. Additionally, an algorithm to maximise the average throughput of the secondary system over a given slot time is given. Increased throughput allows to improve the energy harvesting in the femtocell. Moreover, the effect of varying the different parameters such as the spatial density of BSs, significantly affects the values of energy harvesting in cognitive femtocell network. The obtained results of simulation tests confirm the obtained theoretical results of energy harvesting in cognitive femtocell networks.

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Authors and Affiliations

  1. Institute of Computer Science, Faculty of Mathematics and Computer Science, Jagiellonian University, ul. Prof. S. Lojasiewicza 6, 30-348, Cracow, Poland

    Jerzy Martyna

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  1. Jerzy Martyna
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Correspondence to Jerzy Martyna .

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Editors and Affiliations

  1. Tampere University of Technology, Tampere, Finland

    Olga Galinina

  2. Tampere University of Technology, Tampere, Finland

    Sergey Andreev

  3. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  4. Tampere University of Technology, Tampere, Finland

    Yevgeni Koucheryavy

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Martyna, J. (2018). Performance Analysis of Cognitive Femtocell Network with Ambient RF Energy Harvesting. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_24

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  • DOI: https://doi.org/10.1007/978-3-030-01168-0_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01167-3

  • Online ISBN: 978-3-030-01168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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