Cluster Computing

, Volume 22, Supplement 4, pp 7705–7712 | Cite as

Performance of spectrum sharing cognitive radio network based on MIMO MC-CDMA system for medical image transmission

  • B. RammyaaEmail author
  • K. S. Vishvaksenan
  • Sumathi Poobal


Cognitive radio (CR) is a futuristic technology which efficiently uses the underutilized TV band spectrum for mobile communication. The spectrum scarcity issue, mobile traffic due to ever-increasing number of clients utilizing the same spectrum and interference problems will be efficiently handled by CR networks. In this paper, we employ CR spectrum for safe transmission of medical reports consisting of magnetic resonance imaging (MRI) scanned images. An effective image encryption algorithm named Arnold cat-map (ACM) transform is used in order to prevent unauthorized alterations in the MRI scanned image by any un-authenticated personnel. Further, we upgrade the resolution of the MRI scanned image by super-resoluting it by SPARSE super-resolution technique. Furthermore, we analyze the transmission of MRI scanned image by considering turbo code as channel encoder. We incorporate space time block code (STBC) as multiple-input and multiple-output (MIMO) profile due to its supremacy in spatial diversity and code division multiple access (CDMA) for simultaneous data transmission to numerous users, for transmission of the MRI scanned report. We utilize CR sub-band frequency to realize multi-carrier (MC) communication and to generate orthogonal spread-spectrum. Furthermore, we also analyse the error rate performance of the system for various Stanford University Interim (SUI) channel models. Finally, from the simulations we divulge that CR defined MIMO MC-CDMA system obtain MRI image with enhanced resolution and upgraded privacy when communicating through realistic channel model specifications.


Code division multiple-access (CDMA) Multi-carrier modulation (MCM) Multi-user interference (MUI) Multiple input multiple output (MIMO) Turbo decoder 


  1. 1.
    Kim, S., Sung, W.: Operational algorithm for wireless communication systems using cognitive radio, In: Proceedings of the International IEEE Conference on Communications, Networks and Satellite (COMNETSAT), pp. 29–33 (2014)Google Scholar
  2. 2.
    Xiao, J., Ye, F., Tian, T., Hu, R.Q.: CR enabled TD-LTE within TV white space system level performance analysis. In: Proceedings of the International IEEE Conference on Global Communications (GLOBECOM) (2011)Google Scholar
  3. 3.
    Shahrokh, H., Mohamed, K.: A new structure for NC-MC-CDMA in cognitive radio networks. In: Proceedings of the 9th International Symposium on Communication and Information Technologies, pp. 653–657 (2009)Google Scholar
  4. 4.
    Attar, A., Nakhai, M.R., Hamid Aghvami, A.: Cognitive radio transmission based on direct sequence MC-CDMA. IEEE Trans. Wirel. Commun. 7(4), 1157–1162 (2008)CrossRefGoogle Scholar
  5. 5.
    Kabir, M.A., Kaiser, M.S.: Outage Capacity analysis of MC-CDMA based on cognitive radio network. In: Proceedings of the 2nd International Conference on Electrical Engineering and Information and Communication Technology (ICEEICT), (2014)Google Scholar
  6. 6.
    Jasbi, F., So, D.K.C.: Hybrid overlay/underlay cognitive radio network with MC-CDMA. IEEE Trans. Veh. Technol. 65(4), 2038–2047 (2016)CrossRefGoogle Scholar
  7. 7.
    Rajabzadeh, M., Khoshbin, H.: Receiver design for downlink MIMO MC-CDMA in Cognitive Radio systems. In: proceedings of the 21st International IEEE symposium on Personal, Indoor and Mobile radio communications, pp. 786–790 (2010)Google Scholar
  8. 8.
    Zhou, R., Li, X., Chakravarthy, V., Wu, Z.: Software defined radio implementation of SMSE based overlay cognitive radio in high mobility environment. In: Proceedings of the International IEEE Conference on Global Communications (GLOBECOM) (2011)Google Scholar
  9. 9.
    Tadrous, J., Sultan, A., Mohammed, N.: Admission and power control for spectrum sharing cognitive radio networks. IEEE Trans. Wirel. Commun. 10(6), 1945–1955 (2011)CrossRefGoogle Scholar
  10. 10.
    Yang, J., Wright, J., Huang, T.S., Ma, Y.: Image super-resolution via sparse representation. In: Proceedings of the IEEE Transactions on Image Processing, vol. 19, no. 11, pp. 2861–2873 (2010)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Kim, K.I., Kwon, Y.: Single-image super-resolution using sparse regression and natural image prior. IEEE Trans. Pattern Anal. Mach. Intell. 32(6), 1127–1133 (2010)CrossRefGoogle Scholar
  12. 12.
    Xiao, D., Liao, X., Wei, P.: Analysis and Improvement of a chaos based image encryption algorithm. Elseveir J. Chaos Sol. Fractals 40(5), 2191–2199 (2009)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Tang, Z., Zhang, X.: Secure image encryption without size limitation using Arnold transform and random statergies. J. Multimed. 6(2), 202–206 (2011)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Essaid, M., Jarjar, A., Akharraz, A.S., Mouhib, A.: Image encryption based on Arnold transformation. Gulf J. Math. 4(4), 103–107 (2016)MathSciNetzbMATHGoogle Scholar
  15. 15.
    Alamouti, S.M.: A simple transmitter diversity scheme for wireless communications. IEEE J. Sel. Areas Commun. 16(8), 1451–1458 (1998)CrossRefGoogle Scholar
  16. 16.
    Femenias, G.: BER performance of linear STBC from orthogonal designs over MIMO correlated Nakagami-\(m\) fading channels. IEEE Trans. Veh. Technol. 53(2), 307–17 (2004)CrossRefGoogle Scholar
  17. 17.
    Lam, S., Kostas, N.: Plataniotis and Subbarayan Pasupathy. Self-matching space-time block codes for matrix Kalman estimator-based ML detector in MIMO fading channels. IEEE Trans. Veh. Technol. 56, 2130–2142 (2007)CrossRefGoogle Scholar
  18. 18.
    Abdaoui, A., Ikki, S.S., Ahmed, M.H., Chatelet, E.: On the performance analysis of a MIMO-relaying scheme with space–time block codes. IEEE Trans. Veh. Technol. 59, 3604–3609 (2010)CrossRefGoogle Scholar
  19. 19.
    Tarokh, V., Jafarkhani, H., Calderbank, A.R.: Space-time block codes from orthogonal designs. IEEE Trans. Inf. Theory 45(5), 1456–1467 (1999)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Vishvaksenan, K.S., Seshasayanan, R., Krishnamoorthy, Y.: Performance of joint transmit scheme assisted multiple-input multiple-output multi-carrier IDMA system. J. Comput. Elect. Eng. 39(3), 984–995 (2013)CrossRefGoogle Scholar
  21. 21.
    Vishvaksenan, K.S., Seshasayanan, R., Subramanian, S.: Performance of dual-polarized DSTTD-IDMA system over correlated frequency selective channels. J. Comput. Elect. Eng. 40, 1296–1305 (2014)CrossRefGoogle Scholar
  22. 22.
    Wolkerstorfer, M., Statovci, D., Nordstrom, T.: Enabling greener DSL access networks by their stabilization with artificial noise and SNR margin. J. Clust. Comput. 16, 407–419 (2013)CrossRefGoogle Scholar
  23. 23.
    Mithra, K., Vishvaksenan, K.S.: Performance of coded STBC-IDMA system using polarization diversity for downlink transmission. J. Clust. Comput. 20, 1615–1623 (2017)CrossRefGoogle Scholar
  24. 24.
    Maucher, J., Furrer, J., Heise: IEEE Std. 2007, IEEE Standard for WIMAX 802.16, Hannover (2007)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • B. Rammyaa
    • 1
    Email author
  • K. S. Vishvaksenan
    • 2
  • Sumathi Poobal
    • 3
  1. 1.Department of EIEKCG College of TechnologyChennaiIndia
  2. 2.Department of ECESSN College of EngineeringChennaiIndia
  3. 3.Department of ECEKCG College of TechnologyChennaiIndia

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