Performance Analysis of Wireless Powered Cognitive Radio Networks

  • Thanh-Duc Le
  • Hong-Nhu Nguyen
  • Si-Phu Le
  • Dinh-Thuan DoEmail author
  • Jaroslav Zdralek
  • Miroslav Voznak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 612)


In this paper, we design a energy harvesting-assisted relay which collects energy from signals radiated by PU (primary user) transmitters, then SU (secondary user) transmitters can be used to forward signal to PU receivers. In this model, transmit power of PU transmitters are divided into two equal part for primary network and secondary network in cognitive radio. This paper will discuss how to evaluate system performance under impacts of energy harvesting coefficients through the outage performance. Such analytical expression can be verified through Monte-Carlo simulation to confirm advantage of the proposed model.



This research is funded by Foundation for Science and Technology Development of Ton Duc Thang University (FOSTECT), website:, under grant number FOSTECT.2016.BR21.


  1. 1.
    Do, D.-T.: Energy-aware two-way relaying networks under imperfect hardware: optimal throughput design and analysis. Telecommun. Syst. J. 62(2), 449–459 (2015). SpringerCrossRefGoogle Scholar
  2. 2.
    Do, D.-T.: Optimal throughput under time power switching based relaying protocol in energy harvesting cooperative network. Wireless Pers. Commun. 87(2), 551–564 (2016). SpringerCrossRefGoogle Scholar
  3. 3.
    Hua, S., Liu, H., et al.: Exploiting MIMO antennas in cooperative cognitive radio networks. In: IEEE INFOCOM, pp. 2714–2722, April 2011Google Scholar
  4. 4.
    Chen, H., Li, Y., et al.: Distributed power splitting for SWIPT in relay interference channels using game theory. IEEE Trans. Wireless Commun. 14(1), 410–420 (2015)CrossRefGoogle Scholar
  5. 5.
    Zhang, R., Ho, C.K.: MIMO broadcasting for simultaneous wireless information and power transfer. IEEE Trans. Wireless Commun. 12(5), 1989–2001 (2013)CrossRefGoogle Scholar
  6. 6.
    Lu, X., Wang, P., et al.: Wireless networks with RF energy harvesting: a contemporary survey. IEEE Commun. Surv. Tutorials 17(2), 757–789 (2015)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Yin, S., Qu, Z., Li, S.: Achievable throughput optimization in energy harvesting cognitive radio systems. IEEE. J. Sel. Areas Commun. 33(3), 407–422 (2015)Google Scholar
  8. 8.
    Lee, S., Zhang, R., Huang, K.: Opportunistic wireless energy harvesting in cognitive radio networks. IEEE Trans. Wireless Commun. 12(9), 4788–4799 (2013)CrossRefGoogle Scholar
  9. 9.
    Pratibha, M., Li, K.H., Teh, K.C.: Channel selection in multichannel cognitive radio systems employing RF energy harvesting. IEEE Trans. Veh. Technol. 65(1), 457–462 (2016)CrossRefGoogle Scholar
  10. 10.
    Zhai, C., Liu, J., Zheng, L.: Cooperative spectrum sharing with wireless energy harvesting in cognitive radio network. IEEE Trans. Veh. Technol. 65(7), 5303–5316 (2016)CrossRefGoogle Scholar
  11. 11.
    Hoang, D.T., Niyato, D., Wang, P., Kim, D.I.: Performance optimization for cooperative multiuser cognitive radio networks with RF energy harvesting capability. IEEE Trans. Wireless Commun. 14(7), 3614–3629 (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Thanh-Duc Le
    • 1
    • 2
  • Hong-Nhu Nguyen
    • 1
    • 2
  • Si-Phu Le
    • 2
    • 3
  • Dinh-Thuan Do
    • 4
    Email author
  • Jaroslav Zdralek
    • 2
  • Miroslav Voznak
    • 2
  1. 1.HCM City Economic and Technical CollegeHo Chi Minh CityVietnam
  2. 2.VSB Technical University of OstravaOstrava, PorubaCzech Republic
  3. 3.Van Lang UniversityHo Chi Minh CityVietnam
  4. 4.Wireless Communications Research Group, Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam

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