Skip to main content

Advertisement

SpringerLink
Log in

Allocation of optimal energy in an energy-harvesting cooperative multi-band cognitive radio network

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

This paper studies the achievable total throughput of an energy harvesting cooperative cognitive radio (CR) network. A CR transmitter cooperates with a primary user (PU) transmission if PU is found to be present in the given channel while it transmits its own data in the absence of PU. The CR transmitter is an energy harvesting node which harvests simultaneously from non-RF signal as well as RF signal of PU. The CR transmitter uses the harvested energy on shared basis for cooperation and transmission. The same study is also extended for cooperation of multiple CRs in multiple PU band scenario. In cooperation in muti-band scenario, all CRs sense all PU channels and sensing informations are fused at fusion centre to know about the status of PU. Performance is investigated in terms of total network throughput for several parameters such as sensing time, energy splitting parameter, and energy allocation ratio etc. Novel analytical expressions for total useful throughput and optimal energy allocation ratio parameter under the considered network scenario are developed. Useful throughput and optimal energy allocation ratio parameter are also estimated for a target secondary network (CR network) throughput under a quality of service constraint of PU such as collision probability. It is observed that the value of optimal energy allocation parameter gets reduced if the number of CRs in cooperation increases or the number of PU channels increases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Amjad, M., Rehmani, M. H., & Shiwen, M. (2018). Wireless multimedia cognitive radio networks: A comprehensive survey. IEEE Communications Surveys and Tutorials, 20(2), 1056–1103.

    Article  Google Scholar 

  2. Nitti, M., Murroni, M., Fadda, M., & Atzori, L. (2016). Exploiting social internet of things features in cognitive radio. IEEE Access, 4, 9204–9212.

    Article  Google Scholar 

  3. Liang, Y. C., Zeng, Y., Peh, E. C. Y., & Tuan Hong, A. (2008). Sensing-throughput tradeoff for cognitive radio networks. transactions on Wireless Communications, 7(4), 1326–1337.

    Article  Google Scholar 

  4. Wu, Y., & May, T. D. H. K. (2011). Energy efficient spectrum sensing and transmission for cognitive radio system. IEEE Communications Letters, 15(5), 545–547.

    Article  Google Scholar 

  5. Jaein, K., Lee, H., Song, C., Taeseok, O., & Lee, I. (2017). Sum throughput maximization for multi-user MIMO cognitive wireless powered communication networks. IEEE Transactions on Wireless Communications, 6(2), 913–923.

    Google Scholar 

  6. Cai, L., Poor, H., Liu, Y., Luan, T., Shen, X., & Oct, M. J. (2011). Dimensioning network deployment and resource management in green mesh networks. IEEE Communications Letters, 18(5), 58–65.

    Google Scholar 

  7. Mao, S., Cheung, M. H., & Wong, V. (2012). An opimal energy allocation algorithm for energy harvesting wireless sensor networks. In Proceedings of IEEE international conference on communications (ICC12) (pp. 265–270).

  8. Chatterjee, S., Maity, S. P., & Acharya, T. (2015). On opimal sensing time and power allocation for energy efficient cooperative cognitive radio networks. In Proceedings of IEEE ANTS 2015 (pp. 1–6).

  9. Park, S., & Hong, D. (2014). Achievable throughput of energy harvesting cognitive radio networks. IEEE Transactions on Wireless Communications, 13(2), 1010–1022.

    Article  Google Scholar 

  10. Bhowmick, A., Roy, S. D., & Kundu, S. (2015). Performance of secondary User with combined RF and non-RF based energy-harvesting in cognitive radio network. In Proceedings of IEEE ANTS (pp. 1–3).

  11. Liu, X., Li, F., & Na, Z. (2017). Optimal resource allocation in simultaneous cooperative spectrum sensing and energy harvesting for multichannel cognitive radio. IEEE Access, 5, 3801–3812.

    Article  Google Scholar 

  12. Yang, J., Ulukus, S. (2012). Optimal packet scheduling in an energy harvesting communication system. IEEE Transactions on Communications, 60(1), 220–230.

    Article  Google Scholar 

  13. Tutuncuoglu, K., & Yener, A. (2012). Optimum transmission policies for battery limited energy harvesting nodes. IEEE Transactions on Wireless Communications,11(3), 1180–1189.

    Article  Google Scholar 

  14. Shafie, A. E., Ashour, M., Khattab, T., & Mohamed, A. (2015). On spectrum sharing between energy harvesting cognitive radio users and primary users. In Proceedings of international conference on computing, networking and communications (ICNC), IEEE, Garden Grove, CA (pp. 214–220).

  15. Zhai, C., Liu, J., & Zheng, L. (2016). Relay-based spectrum sharing with secondary users powered by wireless energy harvesting. IEEE Transactions on Communications, 64(5), 1875–1887.

    Article  Google Scholar 

  16. Kalamkar, S. S., Jeyaraj, J. P., Banerjee, A., & Rajawat, K. (2016). Resource allocation and fairness in wireless powered cooperative cognitive radio networks. IEEE Transactions on Communications, 64(8), 3246–3261.

    Article  Google Scholar 

  17. Liu, X., Li, F., & Na, Z. (2016). Optimal resource allocation in simultaneous cooperative spectrum sensing and energy harvesting for multichannel cognitive radio. IEEE Access, 5, 3801–3812.

    Article  Google Scholar 

  18. Hong, X., Kang, X., Wong, K.-K., & Nallanathan, A. (2017). Optimizing DF cognitive radio networks with full-duplex-enabled energy access points. IEEE Transactions on Wireless Communications, 16(7), 4683–4697.

    Article  Google Scholar 

  19. Yao, Y., Yin, C., Song, X., & Beaulieu, N. C. (2016). Increasing throughput in energy-based opportunistic spectrum access energy harvesting cognitive radio networks. Journal of Communications and Networks, 18(3), 340–350.

    Article  Google Scholar 

  20. Chi, X., Zheng, M., Liang, W., Haibin, Y., & Liang, Y.-C. (2017). End-to-end throughput maximization for underlay multi-hop cognitive radio networks with RF energy harvesting. IEEE Transactions on Wireless Communications, 16(6), 3561–3572.

    Article  Google Scholar 

  21. El Shafie, A., & Sultan, A. (2013). Optimal random access for a cognitive radio terminal with energy harvesting capability. Journal of Communications and Networks, 17(6), 1128–1131.

    Google Scholar 

  22. Michele, S., & Maurizio, M. (2010). Nonconvex optimization of collaborative multiband spectrum sensing for cognitive radios with genetic algorithms. International Journal of Digital Multimedia Broadcasting, 2010, 1–12.

    Google Scholar 

  23. Furtado, A., Irio, L., Oliveira, R., Bernardo, L., & Dinis, R. (2016). Spectrum sensing performance in cognitive radio networks with multiple primary users. IEEE Transactions on Vehicular Technology, 65(3), 1564–1574.

    Article  Google Scholar 

  24. Si, J., Li, Z., Yang, D., & Yan, Z. (2015). Parallel cooperative sensing in multichannel cognitive radio networks with partial CSI. International conference on wireless communications & signal processing (WCSP). (pp. 1–6).

  25. Boulogeorgos, A. A., Chatzidiamantis, N. D., & Karagiannidis, G. K. (2016). Spectrum sensing with multiple primary users over fading channels. IEEE Communications Letter, 20(7), 1457–1460.

    Google Scholar 

  26. Ejaz, W., & Ibnkahla, M. (2018). Multiband Spectrum sensing and resource allocation for IoT in cognitive 5G networks. IEEE Internet of Things Journal, 5(1), 150–163.

    Article  Google Scholar 

  27. Zhang, R., & Ho, C. K. (2013). MIMO broadcasting for simultaneous wireless information and power transfer. IEEE Transactions on Wireless Communications, 12(5), 1989–2001.

    Article  Google Scholar 

  28. Nasir, A. A., Zhou, S. D., Durrani, S., & Kennedy, R. A. (2014). Throughput and ergodic capacity of wireless energy harvesting based DF relaying network. In Proceedings of IEEE international conference on communications (ICC14) (pp. 4066–4071).

  29. Zhiping, S., Kah, C. T., & Kwok, H. L. (2013). Energy efficient joint design of sensing and transmission durations for protection of primary user in cognitive radio systems. IEEE Communications Letters, 17(3), 565–568.

    Article  Google Scholar 

  30. Liu, Y., & Tewfik, A. (2014). Primary traffic characterization and secondary transmissions. IEEE Transactions on Wireless Communications, 13(6), 3003–3016.

    Article  Google Scholar 

  31. Bhowmick, A., Sanjay, D. R., & Kundu, S. (2016). Throughput of a cognitive radio network with energy-harvesting based on primary user signal. IEEE Wireless Communications Letter, 5(2), 136–139.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SENSE, VIT University, Vellore, TN, India

    Abhijt Bhowmick

  2. Department of ECE, BCET, Durgapur, WB, India

    Gopal Chandra Das

  3. Department of ECE, NIT Durgapur, Durgapur, India

    Sanjay Dhar Roy & Sumit Kundu

  4. Department of IT, IIEST, Shibpur, WB, India

    Santi P. Maity

Authors
  1. Abhijt Bhowmick
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gopal Chandra Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sanjay Dhar Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sumit Kundu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Santi P. Maity
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abhijt Bhowmick.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bhowmick, A., Das, G.C., Roy, S.D. et al. Allocation of optimal energy in an energy-harvesting cooperative multi-band cognitive radio network. Wireless Netw 26, 1033–1043 (2020). https://doi.org/10.1007/s11276-018-1849-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-018-1849-2

Keywords

Search

Navigation