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An Interpolation-Based Approach to Time-Varying Equalizer Design

  • Muhammad Qaisrani
Research Article - Electrical Engineering
  • 11 Downloads

Abstract

Communications over time-varying channels entail receiver designs which adapt themselves to the channel temporal variations and consequently pose significant computational requirements for the receiver. This work studies the equalization of such channels from the perspective of the computational complexities involved and proposes a flexible, low-complexity scheme for the design of time-varying equalizers based on reconstructing the time-varying equalizer from its samples through a combination of the Fourier exponentials and the Gradient Descent algorithm. This approach is considered for both linear and decision feedback equalizer designs. It is further extended to the framework of turbo equalization for time-varying channels. Numerical simulations have been performed to evaluate the performance of this proposed scheme, while a detailed complexity analysis shows that the proposed scheme can result in significant simplification in the receiver design complexity without incurring much performance loss.

Keywords

Time-varying Low complexity Equalization Doubly selective channels Gradient descent 

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References

  1. 1.
    Mecklenbrauker, C.F. et. al.: Vehicular channel characterization and its implications for wireless system design and performance. In: Proceedings of the IEEE, pp. 1189-1212 (2011)Google Scholar
  2. 2.
    Schniter, P.: Low complexity equalization of OFDM in doubly selective channels. IEEE Trans. Signal Process. 52, 1002–1011 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Das, S.; Schniter, P.: Max SINR ISI/ICI shaping multicarrier communication over the doubly dispersive channel. IEEE Trans. Signal Process. 55, 5782–5795 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Fang, K.; Rugini, L.; Leus, G.: Block transmissions over doubly selective channels: iterative channel estimation and turbo equalization. EURASIP J. Adv. Signal Process. (2010).  https://doi.org/10.1155/2010/974652
  5. 5.
    Vlachos, E.; Lalos, A.; Berberidis, K.: Low complexity OSIC equalization for OFDM based vehicular communications. IEEE Trans. Veh. Technol. 66, 3765–3776 (2016)Google Scholar
  6. 6.
    Tong, J.; Schreier, P.: Regularized preconditioning for Krylov subspace equalization of OFDM systems over doubly selective channels. IEEE Wirel. Commun. Lett. 2, 367–370 (2013)CrossRefGoogle Scholar
  7. 7.
    Lalos, A.; Kekatos, V.; Berberidis, K.: Adaptive conjugate gradient DFEs for wideband MIMO systems. IEEE Trans. Signal Process. 57, 2406–2412 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Chan, T.; Wan, W.: Analysis of projection methods for solving linear systems with multiple right hand sides. SIAM J. Sci. Comput. 18, 1698–1721 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Wu, N.; Yuan, W.; Wang, H.; Shi, Q.; Kuang, J.: Frequency domain iterative message passing receiver for faster-than-Nyquist signaling in doubly selective channels. IEEE Wirel. Commun. Lett. 5, 584–587 (2016)CrossRefGoogle Scholar
  10. 10.
    Yuan, W.; Wu, N.; Wang, H.; Kuang, J.: Variational inference based frequency domain equalization for faster-than-Nyquist signaling in doubly selective channels. IEEE Signal Process. Lett. 23, 1270–1274 (2016)CrossRefGoogle Scholar
  11. 11.
    Pena-Campos, F.; Parra-Michel, R.; Kantorovich, V.: A low complexity multicarrier system over doubly selective channels using virtual trajectories receiver. IEEE Trans. Wirel. Commun. 15, 5206–5217 (2016)CrossRefGoogle Scholar
  12. 12.
    Ait-Idir, T.; Saudi, S.; Naja, N.: Space time turbo equalization with successive interference cancellation for frequency selective MIMO channels. IEEE Trans. Veh. Technol. 57, 2766–2778 (2008)CrossRefGoogle Scholar
  13. 13.
    Cai, X.; Giannakis, G.: Bounding performance and suppressing intercarrier interference in wireless mobile OFDM. IEEE Trans. Commun. 51, 2047–2056 (2003)CrossRefGoogle Scholar
  14. 14.
    Kim, H.; Tugnait, J.: Turbo equalization for doubly selective fading channels using nonlinear Kalman filtering and basis expansion models. IEEE Trans. Wirel. Commun. 9, 2076–2087 (2010)CrossRefGoogle Scholar
  15. 15.
    Hijazi, H.; Ros, L.: Joint data QR detection and Kalman estimation for OFDM time varying Rayleigh channel complex gains. IEEE Trans. Commun. 58, 170–178 (2010)CrossRefGoogle Scholar
  16. 16.
    Song, L.; Tugnait, J.: Doubly selective fading channel equalization: a comparison of Kalman filter approach with BEM equalizers. IEEE Trans. Wirel. Commun. 8, 60–65 (2009)CrossRefGoogle Scholar
  17. 17.
    Barhumi, I.: Soft output decision feedback equalization for OFDM over doubly selective channels. IET Commun. 15, 1890–1897 (2010)MathSciNetzbMATHGoogle Scholar
  18. 18.
    Barhumi, I.: Turbo equalization of doubly selective channels. Wirel. Commun. Mobile Comput. 14, 1691–1703 (2012)CrossRefGoogle Scholar
  19. 19.
    Barhumi, I.; Moonen, M.: Time varying FIR equalization for MIMO transmissions over doubly selective channels. EURASIP J. Adv. Signal Process. (2010).  https://doi.org/10.1155/2010/704350
  20. 20.
    Barhumi, I.; Leus, G.; Moonen, M.: Time varying FIR equalization of doubly selective channels. IEEE Trans. Wirel. Commun. 4, 202–214 (2005)CrossRefGoogle Scholar
  21. 21.
    Qaisrani, M.; Barhumi, I.: A low Complexity approach to equalization for doubly selective channels. Wirel. Commun. Mobile Comput. 15, 1882–1896 (2014)CrossRefGoogle Scholar
  22. 22.
    Barhumi, I.: MLSE and MAP equalization for transmission over doubly selective channels. IEEE Trans. Veh. Technol. 58, 4120–4128 (2009)CrossRefGoogle Scholar
  23. 23.
    Mostofi, Y.; Cox, D.: ICI mitigation for pilot aided OFDM mobile systems. IEEE Trans. Wirel. Commun. 4, 765–774 (2005)CrossRefGoogle Scholar
  24. 24.
    Pena-Campos, F.; Carrasco-Alvarez, R.; Longoria-Gandara, O.; Parra-Michel, R.: Estimation of fast time varying channels in OFDM systems using two dimensional prolate. IEEE Trans. Wirel. Commun. 12, 898–907 (2013)CrossRefGoogle Scholar
  25. 25.
    Kwak, K.; Lee, S.; Min, H.; Choi, S.; Hong, D.: New OFDM channel estimation with dual-ICI cancelation in highly mobile channel. IEEE Trans. Wirel. Commun. 9, 3155–3165 (2010)CrossRefGoogle Scholar
  26. 26.
    Tse, D.; Viswanath, P.: Fundamentals of Wireless Communications. Cambridge University Press, Cambridge (2005)CrossRefzbMATHGoogle Scholar
  27. 27.
    Jakes, W.: Microwave Mobile Communications. Wiley, Hoboken (1974)Google Scholar
  28. 28.
    Nesterov, Y.: Introductory Lectures on Convex Optimization. Springer, Berlin (2003)zbMATHGoogle Scholar
  29. 29.
    Tuchler, M.; Singer, S.; Koetter, R.: Turbo equalization: principles and new results. IEEE Trans. Commun. 50, 754–766 (2002)CrossRefGoogle Scholar
  30. 30.
    Rafati, A.; Lou, H.; Xiao, C.: Low complexity soft decision feedback turbo equalization for MIMO systems with multilevel modulations. IEEE Trans. Veh. Technol. 60, 3218–3227 (2011)CrossRefGoogle Scholar
  31. 31.
    Muneer, P.; Sameer, S.: Iterative Joint carrier frequency offset and doubly selective channel estimation in high mobility MIMO-OFDMA uplink using oblique projection. IEEE Trans. Veh. Technol. 65, 7110–7121 (2015)CrossRefGoogle Scholar
  32. 32.
    Zemen, T.; Bernado, L.; Czink, N.; Molisch, A.F.: Iterative time variant channel estimation for 802.11p using generalized discrete prolate spheroidal sequences. IEEE Trans. Veh. Technol. 61, 1222–1233 (2012)CrossRefGoogle Scholar
  33. 33.
    Song, L.; Lei, X.; Yu, F.; Jin, M.: Optimal complex exponentials BEM and channel estimation in doubly selective channel. Chaos Solitons Fractals 89, 465–473 (2016)CrossRefzbMATHGoogle Scholar
  34. 34.
    Movahedian, A.; McGuire, M.: Estimation of fast fading channels for turbo receivers with high order modulations. IEEE Trans. Veh. Technol. 62, 667–678 (2013)CrossRefGoogle Scholar
  35. 35.
    Guo, Q.; Ping, L.; Huang, D.: A low complexity iterative channel estimation and detection technique for doubly selective channels. IEEE Trans. Wirel. Commun. 8, 4340–4349 (2009)CrossRefGoogle Scholar
  36. 36.
    Ma, X.; Giannakis, G.; Ohno, S.: Optimal training for block transmissions over doubly selective wireless fading channels. IEEE Trans. Signal Process. 51, 1351–1366 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  37. 37.
    Tugnait, J.; et al.: Doubly selective channel estimation using exponential basis models and subblock tracking. IEEE Trans. Signal Process. 58, 1275–1289 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  38. 38.
    Li, C.; Yang, L.; Zhu, W.-P.: A two-way MIMO relaying scheme with partial channel state information. Wirel. Pers. Commun. 72, 1949–1968 (2013)CrossRefGoogle Scholar
  39. 39.
    Li, C.; Yangm, L.; Zhu, W.-P.: Minimum mean square error design of single antenna two-way distributed relays based on full or partial channel state information. IET Commun. 5, 728–735 (2011)MathSciNetCrossRefGoogle Scholar
  40. 40.
    Li, C.; Yang, H.J.; Sun, F.; Cioffi, J.; Yang, L.: Multiuser overhearing for cooperative two-way multiantenna relays. IEEE Trans. Veh. Technol. 65, 3796–3802 (2016)CrossRefGoogle Scholar
  41. 41.
    Li, C.: Spectral efficient cellular communications with coexistent one and two hop transmissions. IEEE Trans. Veh. Technol. 65, 6765–6772 (2016)CrossRefGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.APCOMS, University of Engineering and Technology - TaxilaRawalpindiPakistan

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