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An enhanced channel estimation technique for CDD OFDM system over time varying channels

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Abstract

Cyclic delay diversity (CDD), employing multiple antennas provides increased frequency-selectivity and thereby achieves frequency diversity using forward error correction in orthogonal frequency division multiplexing (OFDM). However, channel estimation of CDD OFDM becomes crucial over frequency-selective fading channels. In this paper, we propose a low-complexity channel estimation technique for CDD OFDM systems over time-varying channels using basis expansion model. We first analyze the frequency correlation of CDD OFDM channels and then design scattered pilot structure for estimating the channel coefficients. In the proposed channel estimator, Slepian sequences are employed estimate the channel impulse response by exploiting the frequency correlation of CDD OFDM over time-varying channel. Simulation results demonstrated that the proposed channel estimator achieves better mean square error and bit-error-rate performance compared with that of existing methods over time-varying channels.

Keywords

Cyclic delay diversity Orthogonal frequency division multiplexing Spatially correlated channels Slepian sequences 

References

  1. 1.
    Cui, T., Tellambura, C., Wu, Y.: Low-complexity pilot-aided channel estimation for OFDM systems over doubly-selective channels. In: IEEE International Conference on Communications, 2005. ICC 2005, vol. 3, pp. 1980–1984 (2005)Google Scholar
  2. 2.
    Chen, Y.F., Sheen, W.-H., Wang, L.-C.: Optimization of cyclic-delay diversity aided frequency-selective scheduling in OFDMA downlink systems. IEEE Trans. Veh. Technol. 63(4), 1645–1659 (2014)CrossRefGoogle Scholar
  3. 3.
    Zhang, Y., Cosmas, J., Bard, M., Song, Y.H.: Diversity gain for DVB-H by using transmitter receiver cyclic delay diversity. IEEE Trans. Broadcast 52(4), 464–474 (2006)CrossRefGoogle Scholar
  4. 4.
    Rahman, M., Witrisal, K., Das, S., Fitzek, F.H.P., Olsen, O., Prasad, R.: Optimum pre-DFT combining with cyclic delay diversity for OFDM based WLAN systems. In: 2004 IEEE 59th Vehicular Technology Conference, 2004. VTC 2004-Spring, vol. 4, pp. 1844–1848 (2004)Google Scholar
  5. 5.
    Lee, D., Jung, Y.S., Lee, J.H.: Cooperative coding using cyclic delay diversity for OFDM systems. ICICE Trans. Commun. 9, 2354–2362 (2010)CrossRefGoogle Scholar
  6. 6.
    Kim, Y.J., Kim, H.Y., Li, D.W.: On the optimal cyclic delay value in cyclic delay diversity. IEEE Trans. Broadcast. 55(4), 790–795 (2009)CrossRefGoogle Scholar
  7. 7.
    Bauch, G., Malik, J.S.: Cyclic delay diversity with bit-interleaved coded modulation in orthogonal frequency division multiple access. IEEE Trans. Wirel. Commun. 5(8), 2092–2100 (2006)CrossRefGoogle Scholar
  8. 8.
    Auer, G.: Channel estimation for OFDM with cyclic delay diversity. In: 15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2004. PIMRC 2004, vol. 3, pp. 1792–1796 (2004)Google Scholar
  9. 9.
    Auer, G.: Channel estimation by set partitioning for OFDM with cyclic delay diversity. In: Proc. IEEE Veh. Tech. Conf. (2004)Google Scholar
  10. 10.
    Hou, W., Wang, X.: Excessively long channel estimation for CDD OFDM systems using superimposed pilots. In: 2011 IEEE International Conference on Communications (ICC), pp. 1–5 (2011)Google Scholar
  11. 11.
    Lu, S., Al-Dhahir, N.: A novel CDD-OFDM scheme with pilot-aided channel estimation. IEEE Trans. Wirel. Commun. 8(3), 1122–1127 (2009)CrossRefGoogle Scholar
  12. 12.
    Rossi, P.S., Mller, R.R., Edfors, O.: Linear MMSE estimation of time-frequency variant channels for MIMO-OFDM systems. Signal Process. 91(5), 1157–1167 (2011)CrossRefMATHGoogle Scholar
  13. 13.
    Chiong, C., Rong, Y., Xiang, Y.: Channel estimation for time-varying MIMO relay systems. IEEE Trans. Wirel. Commun. 14, 6752–6762 (2015)CrossRefGoogle Scholar
  14. 14.
    Song, F.Y.L., Lei, X., Jin, M.: Optimal complex exponentials BEM and channel estimation in doubly selective channel. Chaos Solitons Fractal 89, 465–473 (2016)CrossRefMATHGoogle Scholar
  15. 15.
    Song, F.Y.L., Lei, X., Jin, M.: Spatial-temporal bem and channel estimation strategy for massive mimo time-varying systems. IEEE Global Communications Conference (GLOBECOM) 2016, 1–6 (2016)Google Scholar
  16. 16.
    Tang, G.L.Z., Cannizzaro, R.C., Banelli, P.: Pilot-assisted time-varying channel estimation for OFDM systems. IEEE Trans. Signal Process 55(5), 2226–2238 (2007)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Zemen, T., Mecklenbrauker, C.: Time-variant channel estimation using discrete prolate spheroidal sequences. IEEE Trans. Signal Process 53(9), 3597–3607 (2005)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Van De Ville, D., Philips, W., Lemahieu, I.: On the N-dimensional extension of the discrete prolate spheroidal window. IEEE Signal Process. Lett. 9, 89–91 (2002)CrossRefGoogle Scholar
  19. 19.
    Rossi, P.S., Muller, R.: Slepian-based two-dimensional estimation of time-frequency variant MIMO-OFDM channels. IEEE Signal Process. Lett. 15, 21–24 (2008)CrossRefGoogle Scholar
  20. 20.
    Rappaport, T.: Wireless Communication: Principles and Practice. Prentice Hall, New Jersey (2002)Google Scholar
  21. 21.
    Tang, S., Gong, K., Song, J., Pan, C., Yang, Z.: Intercarrier interference cancellation with frequency diversity for OFDM systems. IEEE Trans. Broadcast. 53, 132–137 (2007)CrossRefGoogle Scholar
  22. 22.
    Wei, L., Kennedy, R., Lamahewa, T.A.: An optimal basis of band-limited functions for signal analysis and design. IEEE Signal Process. Lett. 58(11), 5744–5755 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Faculty of ElectronicsSathyabama UniversityChennaiIndia
  2. 2.KCG College of TechnologyChennaiIndia
  3. 3.TN GovtChennaiIndia

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