Advertisement

Wireless Networks

, Volume 25, Issue 4, pp 2173–2185 | Cite as

Compensation schemes and performance analysis of jointly nonlinear amplifier and timing errors for CP-OFDM based cognitive radio networks

  • Hanen LajnefEmail author
  • Maha Cherif Dakhli
  • Moez Hizem
  • Ridha Bouallegue
Article
  • 27 Downloads

Abstract

The principal objective of cognitive radio (CR) networks is to configure and share dynamically the spectrum resources in order to avoid user interference and congestion. This goal is limited by the effect of errors synchronization between primary and secondary users. In this paper, we study the impact of the asynchronism on the cyclic prefix-based orthogonal frequency division multiplexing modulation (CP-OFDM) including nonlinear HPA model. The considered system includes a reference primary user perfectly synchronized with its reference base station and Nsu interfering secondary users. We provide a new theoretical aspect of interference analysis in the context of the OFDM based CR network. Furthermore, on the basis of this analysis, we derive the accurate expression of bit error rate in the presence of a Rayleigh flat fading channel. Finally, to solve the problems of asynchronism and nonlinearity, a hybrid iterative method of compensation and parallel interference cancellation have been developed based on these two conditions.

Keywords

Cognitive radio networks CP-OFDM Asynchronous interference HPA NLD Bit error rate 

Notes

Acknowledgements

This research is supported by Innov’Com laboratory. Part of the work was presented at the 16th International Conference on Ad Hoc Networks and Wireless (Adhoc-Now 2017) published in the Springer Lecture Notes in Computer Science (LNCS) [15].

References

  1. 1.
    Mahmoud, H. A., Yucek, T., & Arslan, H. (2009). Ofdm for cognitive radio: Merits and challenges. IEEE Wireless Communications, 16(2), 6–15.CrossRefGoogle Scholar
  2. 2.
    Mitola, J., & Maguire, G. Q. (1999). Cognitive radio for flexible mobile multimedia communications. In IEEE international workshop on mobile multimedia communications (MoMuC’99), pp. 3–10.Google Scholar
  3. 3.
    Dardari, D., Tralli, V., & Tralli, V. (2000). A theoretical characterization of nonlinear distortion effectsin OFDM systems. IEEE Transactions on Communications, 48(10), 1755–1764.CrossRefGoogle Scholar
  4. 4.
    Dakhli, M., Zayani, R., Belkacem, O. B., & Bouallegue, R. (2014). Theoretical analysis and compensation for the joint effects of HPA nonlinearity and RF crosstalk in VBLAST MIMO OFDM systems over Rayleigh fading channel. EURASIP Journal on Wireless Communications and Networking, 2014(6)1, 15 p.Google Scholar
  5. 5.
    Zayani, R., Shaiek, H., Roviras, D., & Medjahdi, Y. (2015). Closed-form ber expression for(qam or oqam)-based ofdm system with hpa nonlinearity over rayleigh fading channel. IEEE Wireless Communications Letters, 4(1), 38–41.CrossRefGoogle Scholar
  6. 6.
    Elmaroud, B., Abbad, M., & Aboutajdine, D. (2016). BER analysis of asynchronous and nonlinear FBMC based multi-cellular networks. In IEEE 27th annual international symposium on personal, indoor, and mobile radio communications (PIMRC).Google Scholar
  7. 7.
    Wang, X. C. X., Chen, H. H., & GuiZani, M. (2008). Cognitive radio network management. IEEE Vehicular Technology Magazine, 3(1), 28–35.CrossRefGoogle Scholar
  8. 8.
    Lajnef, H., Dakhli, M. C., Hizem, M., & Bouallegue, R. (2016). The impact of the nonlinear distortion on OFDM and FBMC signals based cognitive radio applications over Rayleigh fading channel. In IWCMC 2016, pp. 1141–1145.Google Scholar
  9. 9.
    Saeedi-Sourck, H., Wu, Y., Bergmans, J. W., & Sadri, S. (2011). Sensitivity analysisof offset QAM multicarrier systems to residual carrier frequency and timing offsets. Signal Processing, 91(7), 1604–1612.CrossRefzbMATHGoogle Scholar
  10. 10.
    Medjahdi, Y. (2012). Modelisation des interfrence et analyse des performances des systmes OFDM/FBMC pour les communications sans fil asyn-chrones, Ph.D. Thesis, Le CNAM.Google Scholar
  11. 11.
    Aissa, S. B., Hizem, M., & Bouallegue, R. (2017). Interference analysis for asynchrounous OFDM/FBMC based cognitive radio networks over Rayleigh fading channel. In Networks wireless, Springer, vol. 23, pp. 1–14.Google Scholar
  12. 12.
    Hamdi, K. A., & Shobowale, Y. M. (2009). Interference analysis in downlink OFDM considering imperfect intercell synchronization. IEEE Transactions on Vehicular Technology, 58(7), 3283–3291.CrossRefGoogle Scholar
  13. 13.
    Medjahdi, Y., Terré, M., Le Ruyet, D., & Roviras, D. (2014). Interference tables: A useful model for interference analysis in asynchronous multicarrier transmission. Eurasip.Google Scholar
  14. 14.
    Hassan, M. H., & Hossain, M. J. (2013). Cooperative beamforming for CR systems with asynchronous interference to primary user. In IEEE ICC 2013, pp. 5679–5683.Google Scholar
  15. 15.
    Lajnef, H., Dakhli, M. C., Hizem, M., & Bouallegue, R. (2017). Interference analysis for asynchronous OFDM in multi-user cognitive radio networks with ,nonlinear distortions. In AdHocNow2017, LNCS 10517, pp. 382–393.Google Scholar
  16. 16.
    Kobayashi, M., Boutros, J., & Caire, G. (2001). Successive interference cancellation with SISO decoding and EM channel estimation. IEEE Journal on Selected Areas in Communications, 19(8), 1450–1460.CrossRefGoogle Scholar
  17. 17.
    Moussaoui, M., Zaizouni, M., & Rouvaen, M. (2007). Another approach for partial parallel interference cancellation. Wireless Personal Communications, 42(4), 587–606.CrossRefGoogle Scholar
  18. 18.
    Divsalar, D., Simon, M., & Raphaeli, D. (1998). Improved parallel interference cancellation for CDMA. IEEE Transactions on Communications, 46, 258268.CrossRefGoogle Scholar
  19. 19.
    Al-Junaid, A. F., & Al-kamali, F. S. (2016). Efficient wireless transmission scheme based on the recent DST-MC-CDMA. Wireless Networks, 22(3), 813–824.CrossRefGoogle Scholar
  20. 20.
    Shibahara, K., Masuda, A., Kawai, S., & Fukutoku, M. (2015). Multi-stage successive interference cancellation for spectrally-efficient super-Nyquist transmission. In IEEE ECOC 2015.Google Scholar
  21. 21.
    Miridakis, N. I., & Vergados, D. D. (2013). A survey on the successive interference cancellation performance for single-antenna and multiple-antenna OFDM systems. IEEE Communications Surveys & Tutorials, 15(1), 312–333. FIRST QUARTER.CrossRefGoogle Scholar
  22. 22.
    Hamouda, W., & Li, M. (2007). An adaptive MMOE-PIC detector for asynchronous DS-CDMA communications. Wireless Personal Communications, 42(4), 607–618.CrossRefGoogle Scholar
  23. 23.
    Jiang, C., Zhang, H., Han, Z., Cheng, J., Ren, Y., & Hanzo, L. (2016). On the outage probability of information sharing in cognitive vehicular networks. In Proceedings of IEEE international conference on communications (ICC 2016), Kuala Lampur, Malaysia.Google Scholar
  24. 24.
    Hu, Z., Wei, N., et al. (2017). Outage analysis of coded-cooperation cognitive multi-relay network with direct link over Nakagami-m fading channels. Trans. Emerg. Telecommun. Technol., 28(12), e3218.CrossRefGoogle Scholar
  25. 25.
    Lajnef, H., Dakhli, M. Cherif, Hizem, M., & Bouallegue, R. (2016). The effect of the nonlinear distortion on OFDM based cognitive radio systems over rayleigh fading channel. In WAINA, 2016 international. IEEE, 2016, pp. 427–430.Google Scholar
  26. 26.
    Saleh, A. A. M. (1981). Frequency-independent and frequency-dependent nonlinear models of TWT amplifiers. IEEE Transactions on Communications, 29, 1715–1720.CrossRefGoogle Scholar
  27. 27.
    Dakhli, M., Zayani, R., & Bouallegue, R.. (2012). Compensation for nonlinear distortion in MIMO OFDM systems using MMSE receiver. In IEEE 15th international conference on communication systems, ICCS (Singapore 2012).Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Innov’COM Laboratory-Sup’ComUniversity of CarthageTunisTunisia

Personalised recommendations