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Full-Duplex Cognitive Radio with RF Energy Harvesting

  • Hang HuEmail author
  • Xinyu Da
  • Hang Zhang
  • Lei Ni
Article
  • 34 Downloads

Abstract

With the development of self-interference suppression techniques, full-duplex (FD) communication is expected to double the spectrum efficiency (SE). In FD based cognitive radio (CR), the secondary users (SUs) can perform spectrum sensing and data transmission simultaneously, with the goal of achieving better sensing performance or higher throughput for the SUs. Another key performance metric in fifth-generation (5G) wireless networks, energy efficiency (EE), has attracted more and more attention recently. The radio frequency (RF) energy harvesting (EH) technique is proposed to prolong the battery lifetime of low-power communication devices. In this paper, we are interested in the full-duplex CR with energy harvesting. We consider that the SUs can harvest RF energy from the PU and recycle part of its own energy when the secondary data transmission is conducted. The EE of the CR system is defined as the ratio of the average SE over the average power consumption. The system parameters, including the sensing thresholds and the secondary transmit power are optimized to maximize the EE under the constraint that the primary user (PU) is sufficiently protected. Finally, the simulation results are presented to show the outperformance of the proposed FD-EH scheme.

Keywords

Full duplex Cognitive radio Spectrum sensing Energy harvesting 

Notes

Acknowledgements

This work is supported by National Postdoctoral Program for Innovative Talents (No. BX201700108), Natural Science Foundation of Shanxi Province of China (No. 2018JQ6042), China Postdoctoral Science Foundation on the 63th grant program, and the National Natural Science Foundation of China (Grant No. 61671475, Grant No. 61901509, Grant No. 61571460).

References

  1. 1.
    Cheng, W., Zhang, H., Liang, L., Jing, H., & Li, Z. (2018). Orbital-angular-momentum embedded massive MIMO: Achieving multiplicative spectrum-efficiency for mmWave communication. IEEE Access, 6, 2732–2745.CrossRefGoogle Scholar
  2. 2.
    Towhidlou, V., & Shikh-Bahaei, M. (2018). Adaptive full-duplex communications in cognitive radio networks. IEEE Transactions on Vehicular Technology, 67(9), 8386–8395.CrossRefGoogle Scholar
  3. 3.
    Amjad, M., Akhtar, F., Rehmani, M. H., Reisslein, M., & Umer, T. (2017). Full-duplex communication in cognitive radio networks: A survey. IEEE Communications Surveys and Tutorials, 19(4), 2158–2191.CrossRefGoogle Scholar
  4. 4.
    Zhang, R., Chen, H., Yeoh, P. L., Li, Y., & Vucetic, B. (2017). Full-duplex cooperative cognitive radio networks with wireless energy harvesting. In Proceeding of IEEE international conference on communications (ICC) (pp. 1–6).Google Scholar
  5. 5.
    Sharma, S. K., Bogale, T. E., Le, L. B., Chatzinotas, S., Wang, X., & Ottersten, B. (2018). Dynamic spectrum sharing in 5G wireless networks with full-duplex technology: Recent advances and research challenges. IEEE Communications Surveys and Tutorials, 20(1), 674–707.CrossRefGoogle Scholar
  6. 6.
    Pratibha, Li K. H., & Teh, K. C. (2017). Optimal spectrum access and energy supply for cognitive radio systems with opportunistic RF energy harvesting. IEEE Transactions on Vehicular Technology, 66(8), 7114–7122.CrossRefGoogle Scholar
  7. 7.
    Bayat, A., & Aissa, S. (2018). Full-duplex cognitive radio with asynchronous energy-efficient sensing. IEEE Transactions on Wireless Communications, 17(2), 1066–1080.CrossRefGoogle Scholar
  8. 8.
    Li, H., Xu, J., Zhang, R., & Cui, S. (2015). A general utility optimization framework for energy-harvesting-based wireless communications. IEEE Communications Magazine, 53(4), 79–85.CrossRefGoogle Scholar
  9. 9.
    Liang, Y.-C., Chen, K. C., Li, G. Y., & Mahonen, P. (2011). Cognitive radio networking and communications: An overview. IEEE Transactions on Vehicular Technology, 60(7), 3386–3407.CrossRefGoogle Scholar
  10. 10.
    Jiang, C., Beaulieu, N. C., Zhang, L., Ren, Y., Peng, M., & Chen, H.-H. (2015). Cognitive radio networks with asynchronous spectrum sensing and access. IEEE Network, 29(3), 88–95.CrossRefGoogle Scholar
  11. 11.
    Cheng, W., Zhang, X., & Zhang, H. (2011). Imperfect full duplex spectrum sensing in cognitive radio networks. In Proceeding of 3rd ACM workshop on cognitive radio networks (pp. 1–6).Google Scholar
  12. 12.
    Liao, Y., Wang, T., Song, L., & Jiao, B. (2014). Cooperative spectrum sensing for full-duplex cognitive radio networks. In Proceeding of IEEE international conference on communication systems (pp. 56–60).Google Scholar
  13. 13.
    Cheng, W., Zhang, X., & Zhang, H. (2015). Full-duplex spectrum-sensing and MAC-protocol for multichannel nontime-slotted cognitive radio networks. IEEE Journal on Selected Areas in Communications, 33(5), 820–831.CrossRefGoogle Scholar
  14. 14.
    Shafie, A. E., Ashour, M., Khattab, T., & Mohamed, A. (2015). On spectrum sharing between energy harvesting cognitive radio users and primary users. In Proceeding of international conference on computing, networking and communications (pp. 214–220).Google Scholar
  15. 15.
    Zhang, Y., Han, W., Li, D., Zhang, P., & Cui, S. (2015). Power versus spectrum 2-D sensing in energy harvesting cognitive radio networks. IEEE Transactions on Signal Processing, 63(23), 6200–6212.MathSciNetCrossRefGoogle Scholar
  16. 16.
    Pratibha, M., Li, K. H., & Teh, K. C. (2016). Channel selection in multichannel cognitive radio systems employing RF energy harvesting. IEEE Transactions on Vehicular Technology, 65(1), 457–462.CrossRefGoogle Scholar
  17. 17.
    Liao, Y., Wang, T., Song, L., & Han, Z. (2014). Listen-and-talk: full-duplex cognitive radio networks. In Proceeding of IEEE global communications conference (pp. 3068–3073).Google Scholar
  18. 18.
    Peh, E. C. Y., Liang, Y.-C., Guan, Y. L., & Zeng, Y. (2010). Cooperative spectrum sensing in cognitive radio networks with weighted decision fusion schemes. IEEE Transactions on Wireless Communications, 9(12), 3838–3847.CrossRefGoogle Scholar
  19. 19.
    Shi, Z., Teh, K. C., & Li, K. H. (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.CrossRefGoogle Scholar
  20. 20.
    Chapra, Steven C., & Canale, Raymond P. (2010). Numerical methods for engineers (6th ed.). New York: McGraw-Hill.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Information and Navigation CollegeAir Force Engineering UniversityXi’anChina
  2. 2.Yango UniversityFuzhouChina
  3. 3.College of Communications EngineeringArmy Engineering University of PLANanjingChina

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