Advertisement

Wireless Personal Communications

, Volume 101, Issue 2, pp 979–1001 | Cite as

Time-Reversal Based Secure Transmission Scheme for 5G Networks over Correlated Wireless Multi-Path Channels

  • Jiang Zhu
  • Yan Wang
  • Tian Yang
  • Fangwei Li
Article
  • 150 Downloads

Abstract

Broadband wireless communication users for 5G networks are primarily implemented in a complicated environment; the complex environment of time-varying multi-path propagation characteristics will seriously affect the performance of communication. One of the core technologies to overcome this problem is to introduce the environment adaptive technique—time reversal in the wireless link. Further, the problem of a Wiretap Channel in physical layer security research has become a popular research topic in recent years. To resolve the physical layer wiretap channel and multi-path fading problems in wireless channels, a novel concept of combining time reversal technology with physical layer security technology is proposed. In this paper, a physical layer secure transmission scheme based on the joint time reversal technique and artificial noise at the sending end is proposed for the wireless multi-path channel. First, in a typical wiretap channel model, the time reversal technique is used to improve the security of the information transmission process by using the properties of spatial and temporal focusing. Second, as the information is easily eavesdropped near the focus point, artificial noise is added to the sending end to disrupt the eavesdropping capability of the eavesdropper. Finally, due to the complexity of the multi-path channels, the influence of the antenna correlation on the system security performance is considered. Compared with the existing physical layer security schemes, theoretical analysis and simulation results show that the proposed scheme has a higher secrecy signal-to-noise ratio, a higher rate of secrecy, and a lower bit error rate of legitimate user.

Keywords

Wiretap channel Multi-path Time reversal Artificial noise Spatial and temporal focusing Correlation 

Notes

Acknowledgements

This work is supported by the National Nature Science Foundation of China (No. 61771084) and the Nature Science Foundation of Chongqing Science and Technology Commission (No.cstc2015jcyjA40050).

References

  1. 1.
    Yang, H., Bai, W., Yu, A., Zhang, J., & Wang, Z. (2017). Cross-stratum resources integration in fog-Computing-based radio over fiber networks for 5G services. In Opto-electronics and communications conference (OECC) and photonics global conference (PGC), Singapore, Singapore (pp. 1–2).Google Scholar
  2. 2.
    Ejaz, W., & Ibnkahla, M. (2018). Multi-band spectrum sensing and resource allocation for IoT in cognitive 5G networks. In IEEE Internet of Things Journal, 99, 1.Google Scholar
  3. 3.
    Liu, Y., Qin, Z., Elkashlan, M., Ding, Z., Nallanathan, A., & Hanzo, L. (2017). Nonorthogonal multiple access for 5G and Beyond. Proceedings of the IEEE, 105(12), 2347–2381.CrossRefGoogle Scholar
  4. 4.
    Schinianakis, D. (2017). Alternative security options in the 5G and IoT era. IEEE Circuits and Systems Magazine, 17(4), 6–28.CrossRefGoogle Scholar
  5. 5.
    Zhang, J., Podkurkov, I., Haardt, M., & Nadeev, A. (2017). Efficient multidimensional parameter estimation for joint wideband radar and communication systems based on OFDM. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, 2017 (pp. 3096–3100).Google Scholar
  6. 6.
    Proakis, J. G. (2001). Digital communications (4th ed.). New York: McGraw-Hill.zbMATHGoogle Scholar
  7. 7.
    Stuber, G. L. (2001). Principles of mobile communications (2nd ed.). Dordrecht: Kluwer.zbMATHGoogle Scholar
  8. 8.
    Goldsmith, J. (2005). Wireless communication. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  9. 9.
    Tse, D., & Viswanath, P. (2005). Fundamental of wireless communication. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  10. 10.
    Wyner, D. (1975). The wiretap channel. Bell System Technical Journal, 54, 1355–1387.MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Chen, Y., Wang, B., Han, Y., Lai, H. Q., Safar, Z., & Liu, K. J. R. (2016). Why time reversal for future 5G wireless? [perspectives]. IEEE Signal Processing Magazine, 33(2), 17–26.CrossRefGoogle Scholar
  12. 12.
    Han, Y., Chen, Y., Wang, B., & Liu, K. J. R. (2016). Time-reversal massive multi-path effect: A single-antenna, “Massive MIMO” solution. IEEE Transactions on Communications, 64(8), 3382–3394.CrossRefGoogle Scholar
  13. 13.
    Bouzigues, M. A., Siaud, I., Ulmer-Moll, A. M., & Helard, M. (2014). Time reversal and equal gain transmission for 60 GHz millimeter waves orthogonal frequency-division multiplexing systems. In IEEE online conference on green communications (OnlineGreenComm), Tucson, AZ, 2014 (pp. 1–6).Google Scholar
  14. 14.
    Zhai, H., et al. (2010). An electronic circuit system for time-reversal of ultra-wideband short impulses based on frequency-domain approach. IEEE Transactions on Microwave Theory and Techniques, 58(1), 74–86.CrossRefGoogle Scholar
  15. 15.
    Alves, H., Souza, R. D., Debbah, M., & Bennis, M. (2012). Performance of transmit antenna selection physical layer security schemes. IEEE Signal Processing Letters, 19(6), 372–375.CrossRefGoogle Scholar
  16. 16.
    Yang, N., Suraweera, H. A., Collings, I. B., & Yuen, C. (2013). Physical layer security of TAS/MRC with antenna correlation. IEEE Transactions on Information Forensics and Security, 8(1), 254–259.CrossRefGoogle Scholar
  17. 17.
    Tran, D. D., Ha, D. B., Tranha, V., et al. (2015). Secrecy analysis with MRC/SC-based eavesdropper over heterogeneous channels. Iete Journal of Research, 61(4), 363–371.CrossRefGoogle Scholar
  18. 18.
    Al-Moliki, Y., Alresheedi, M., & Al-Harthi, Y. (2017). Physical-layer security against known/chosen plaintext attacks for OFDM-based VLC system. IEEE Communications Letters, 99, 1.Google Scholar
  19. 19.
    Sun, G., Han, Z., Jiao, J., & Wang, D. (2017). Physical layer security in MIMO wiretap channels with antenna correlation. China Communications, 14(8), 149–156.CrossRefGoogle Scholar
  20. 20.
    Feng, Y., Yang, Z., Yan, S., Yang, N. & Lv, B. (2017). Physical layer security enhancement in multi-user multi-full-duplex-relay networks. In IEEE international conference on communications (ICC), Paris (pp. 1–7).Google Scholar
  21. 21.
    Singh, A., Bhatnagar, M. R., & Mallik, R. K. (2017). Physical layer security of a multi-antenna based CR network with single and multiple primary users. IEEE Transactions on Vehicular Technology, 99, 1.Google Scholar
  22. 22.
    Rahmanpour, A., Vakili, V. T., & Razavizadeh, S. M. (2017). Enhancement of physical layer security using destination artificial noise based on outage probability. Wireless Personal Communications, 95, 1–13.CrossRefGoogle Scholar
  23. 23.
    Zhang, L., Zhang, H., Wu, D., & Yuan, D. (2015). Improving physical layer security for MISO systems via using artificial noise. In IEEE global communications conference (GLOBECOM), San Diego, CA, 2015, (pp. 1–6) (Online). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7417842&isnumber=7416057. Accessed Dec 2015.
  24. 24.
    Tesanovic, M., Bucknell, P., & Chebbo, H. (2013). Co-operative use of licensed spectrum by unlicensed devices: The concept of bandwidth scavenging. In IEEE 78th vehicular technology conference (VTC Fall), Las Vegas, NV, (pp. 1–5).Google Scholar
  25. 25.
    Singh, S. K., Bziuk, W., & Jukan, A. (2017). A combined optical spectrum scrambling and defragmentation in multi-core fiber networks. In IEEE international conference on communications (ICC), Paris, (pp. 1–6).Google Scholar
  26. 26.
    Ismael, H. A., & Sadkhan, S. B. (2017). Security enhancement of speech scrambling using triple Chaotic Maps. In Annual conference on new trends in information & communications technology applications (NTICT), Baghdad, (pp. 132–137).Google Scholar
  27. 27.
    Wang, B., & Mu, P. (2017). Artificial noise aided secure multicasting design under secrecy outage constraint. IEEE Transactions on Communications, 99, 1.Google Scholar
  28. 28.
    Wang, B., Mu, P., & Li, Z. (2017). Artificial-noise-aided beamforming design in the MISOME wiretap channel under the secrecy outage probability constraint. IEEE Transactions on Wireless Communications, 99, 1.Google Scholar
  29. 29.
    Mei, W., Chen, Z., & Fang, J. (2017). Artificial noise aided energy efficiency optimization in MIMOME system with SWIPT. IEEE Communications Letters, 21(8), 1795–1798.CrossRefGoogle Scholar
  30. 30.
    Wang, B., Mu, P., Li, Z., Zhang, W., Wang, H. M. & Yin, Q. (2017). Artificial-noise-aided beamforming design against a multi-antenna eavesdropper under secrecy outage constraint. In IEEE international conference on communications (ICC), Paris (pp. 1–6).Google Scholar
  31. 31.
    Yang, M., Zhang, B., Huang, Y., Yang, N., da Costa, D. B., & Guo, D. (2017). Secrecy enhancement of multiuser MISO networks using OSTBC and artificial noise. IEEE Transactions on Vehicular Technology, 99, 1.Google Scholar
  32. 32.
    He, B., She, Y., & Lau, V. K. N. (2017). Artificial noise injection for securing single-antenna systems. IEEE Transactions on Vehicular Technology, 99, 1.Google Scholar
  33. 33.
    Yan, S., Zhou, X., Yang, N., He, B. & Abhayapala, T. D. (2016). Correlation-based power allocation for secure transmission with artificial noise. IEEE Global Communications Conference (GLOBECOM), Washington, DC, (pp. 1–6) (Online). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7841703&isnumber=7841475.
  34. 34.
    Wang, W., Teh, K. C., & Li, K. H. (2017). Artificial noise aided physical layer security in multi-antenna small-cell networks. IEEE Transactions on Information Forensics and Security, 12(6), 1470–1482.CrossRefGoogle Scholar
  35. 35.
    Lei, W. et al. (2016). Physical layer security scheme exploiting artificial noise to improve the performance of legitimate user. Journal of Electronics & Information Technology, 38(11), 2887–2892.Google Scholar
  36. 36.
    Bogdani, E., Vouyioukas, D., Nomikos, N., Skoutas, D. N., & Skianis, C. (2017). Single-point model of MIMO-UWB indoor systems using time-reversal transmission. In IEEE international conference on communications (ICC), Paris (pp. 1–6).Google Scholar
  37. 37.
    Viteri-Mera, C. A., & Teixeira, F. L. (2017). Equalized time reversal beamforming for frequency-selective indoor MISO channels. IEEE Access, 5, 3944–3957.CrossRefGoogle Scholar
  38. 38.
    Ebrahimi-Zadeh, J., Dehmollaian, M. & Mohammadpour-Aghdam, K. (2016). Ultra-wideband electromagnetic DORT time-reversal localization of single-defect in pipe. In 8th International symposium on telecommunications (IST), Tehran, (pp. 409–414).Google Scholar
  39. 39.
    Tran, V., Kaddoum, G., Tran, H., Tran, D. D. & Ha, D. B. (2016). Time reversal SWIPT networks with an active eavesdropper: SER-energy region analysis. In IEEE 84th vehicular technology conference (VTC-Fall), Montreal, QC (pp. 1–5).Google Scholar
  40. 40.
    Han, Y., Chen, Y., Wang, B., & Liu, K. J. R. (2016). Realizing massive MIMO effect using a single antenna: A time-reversal approach. In IEEE global communications conference (GLOBECOM), Washington, DC (pp. 1–6).Google Scholar
  41. 41.
    Mbeutcha, M., Fan, W., Hcjsclbæck, J. & Pedersen, G. F. (2016). Evaluation of massive MIMO systems using time-reversal beamforming technique. In IEEE 27th annual international symposium on personal, indoor, and mobile radio communications (PIMRC), Valencia (pp. 1–6).Google Scholar
  42. 42.
    Zhang, G., & Song, Y. (2016) Time reversal imaging method for damage detection in concrete. In IEEE international conference on signal and image processing (ICSIP), Beijing (pp. 262–266).Google Scholar
  43. 43.
    Zhang, G., & Song, Y. (2016) Novel imaging method based on cross-correlation function for suppressing the interference of noise. In IEEE international conference on signal and image processing (ICSIP), Beijing (pp. 251–255).Google Scholar
  44. 44.
    Cao, W., Lei, J., Liu, W. & Li, X. (2014). Secure performance of time reversal precoding technique in miso OFDM systems. In Communications Security Conference (CSC 2014), Beijing (pp. 1–5) (Online). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6992246&isnumber=6919880.
  45. 45.
    Tan, V. T., Ha, D. B. & Tran, D. D. (2014) Evaluation of physical layer secrecy in MIMO Ultra-WideBand system using Time-Reversal techniques. In International conference on computing, management and telecommunications (ComManTel), Da Nang (pp. 70–74) (Online). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6825581&isnumber=6825559.
  46. 46.
    Wang, B., Wu, Y., Han, F., Yang, Y. H., & Liu, K. J. R. (2011). Green wireless communications: A time-reversal paradigm. IEEE Journal on Selected Areas in Communications, 29(8), 1698–1710.CrossRefGoogle Scholar
  47. 47.
    Simon, M., & Alouini, M. (2000). Digital Communication over Fading Channels. In Digital communication over fading channels. Wiley (pp. 4–5).Google Scholar
  48. 48.
    Hou, J., Zeng, W., Wan, G., Zhou, J., & Sun, M. (2016). The analysis and research on the accuracy of WSN node location under the influence of multi-path reflection. In 35th Chinese control conference (CCC), Chengdu (pp. 8352–8355).Google Scholar
  49. 49.
    Cheng, C. H., Luo, W. J., Lin, Y. W., & Sun, C. C. (2013). Position location techniques in wireless sensor networks using reference node algorithm. In IEEE International Symposium on Consumer Electronics (ISCE), Hsinchu (pp. 73–74).Google Scholar
  50. 50.
    Han, F., Yang, Y. H., Wang, B., Wu, Y., & Liu, K. J. R. (2012). Time-reversal division multiple access over multi-path channels. IEEE Transactions on Communications, 60(7), 1953–1965.CrossRefGoogle Scholar
  51. 51.
    Emami, M., Vu, M., Hansen, J., Paulraj, A. J., & Papanicolaou, G. (2004). Matched filtering with rate back-off for low complexity communications in very large delay spread channels. In Conference record of the thirty-eighth asilomar conference on signals, systems and computers (Vol. 1, pp. 218–222) (Online). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1399123&isnumber=30419.
  52. 52.
    Moose, P. H. (1994). A technique for orthogonal frequency division multiplexing frequency offset correction. IEEE Transactions on Communications, 42(10), 2908–2914.CrossRefGoogle Scholar
  53. 53.
    Lee, J., Lou, H. L., Toumpakaris, D., & Cioffi, J. M. (2006). SNR analysis of OFDM systems in the presence of carrier frequency offset for fading channels. IEEE Transactions on Wireless Communications, 5(12), 3360–3364.CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.School of Communication and Information EngineeringChongqing University of Posts and TelecommunicationsChongqingChina

Personalised recommendations