cogcom 19(14): e5

Research Article

Spectral Efficiency of Energy Harvesting Random Cognitive Radio Networks in Dual-slope Model

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  • @ARTICLE{10.4108/eai.14-1-2019.160388,
    author={Saifur  Rahman  Sabuj and Rakiba  Rayhana and Aldrin  Nippon  Bobby},
    title={Spectral Efficiency of Energy Harvesting Random Cognitive Radio Networks in Dual-slope Model},
    journal={EAI Endorsed Transactions on Cognitive Communications},
    volume={4},
    number={14},
    publisher={EAI},
    journal_a={COGCOM},
    year={2019},
    month={1},
    keywords={Cognitive radio network, Stochastic geometry, Poisson point process, Energy harvesting, and Spectral efficiency},
    doi={10.4108/eai.14-1-2019.160388}
}
  • Saifur Rahman Sabuj
    Rakiba Rayhana
    Aldrin Nippon Bobby
    Year: 2019
    Spectral Efficiency of Energy Harvesting Random Cognitive Radio Networks in Dual-slope Model
    COGCOM
    EAI
    DOI: 10.4108/eai.14-1-2019.160388
Saifur Rahman Sabuj1,*, Rakiba Rayhana2, Aldrin Nippon Bobby1
  • 1: Electrical and Electronic Engineering, BRAC University, Bangladesh
  • 2: Electrical Engineering, The University of British Columbia, Canada
*Contact email: s.r.sabuj@ieee.org

Abstract

This research article evaluates the performance of an energy harvesting random cognitive radio network employing a dual-slope path-loss model in terms of spectral efficiency. It derives the mathematical expression of spectral efficiency by means of stochastic geometry for secondary receivers present in the network in active mode. The numerical result highlights a rise in the efficiency by 20.7% for an increase of 1 dBm in transmit power at a power splitting ratio of 0.5.

Keywords
Cognitive radio network, Stochastic geometry, Poisson point process, Energy harvesting, and Spectral efficiency
Received
2018-12-10
Accepted
2019-01-12
Published
2019-01-14
Publisher
EAI
http://dx.doi.org/10.4108/eai.14-1-2019.160388

Copyright © 2019 Saifur Rahman Sabuj et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.