Skip to main content

Low-Complexity Banded Equalizers for OFDM Systems in Doppler Spread Channels


Recently, several approaches have been proposed for the equalization of orthogonal frequency-division multiplexing (OFDM) signals in challenging high-mobility scenarios. Among them, a minimum mean-squared error (MMSE) block linear equalizer (BLE), based on a band LDL factorization, is particularly attractive for its good tradeoff between performance and complexity. This paper extends this approach towards two directions. First, we boost the BER performance of the BLE by designing a receiver window specially tailored to the band LDL factorization. Second, we design an MMSE block decision-feedback equalizer (BDFE) that can be modified to support receiver windowing. All the proposed banded equalizers share a similar computational complexity, which is linear in the number of subcarriers. Simulation results show that the proposed receiver architectures are effective in reducing the BER performance degradation caused by the intercarrier interference (ICI) generated by time-varying channels. We also consider a basis expansion model (BEM) channel estimation approach, to establish its impact on the BER performance of the proposed banded equalizers.


  1. 1.

    Wang Z, Giannakis GB: Wireless multicarrier communications: where Fourier meets Shannon. IEEE Signal Processing Magazine 2000, 17(3):29–48. 10.1109/79.841722

    Article  Google Scholar 

  2. 2.

    Robertson P, Kaiser S: The effects of Doppler spreads on OFDM(A) mobile radio systems. Proceedings of the 49th IEEE Vehicular Technology Conference (VTC '99), September 1999, Amsterdam, The Netherlands 329–333.

    Google Scholar 

  3. 3.

    Russell M, Stüber GL: Interchannel interference analysis of OFDM in a mobile environment. Proceedings of the 45th IEEE Vehicular Technology Conference (VTC '95), July 1995, Chicago, Ill, USA 820–824.

    Google Scholar 

  4. 4.

    Barhumi I, Leus G, Moonen M: Time-domain and frequency-domain per-tone equalization for OFDM over doubly selective channels. Signal Processing 2004, 84(11):2055–2066. 10.1016/j.sigpro.2004.07.016

    Article  Google Scholar 

  5. 5.

    Cai X, Giannakis GB: Bounding performance and suppressing intercarrier interference in wireless mobile OFDM. IEEE Transactions on Communications 2003, 51(12):2047–2056. 10.1109/TCOMM.2003.820752

    Article  Google Scholar 

  6. 6.

    Choi Y-S, Voltz PJ, Cassara FA: On channel estimation and detection for multicarrier signals in fast and selective Rayleigh fading channels. IEEE Transactions on Communications 2001, 49(8):1375–1387. 10.1109/26.939860

    Article  Google Scholar 

  7. 7.

    Gorokhov A, Linnartz J-P: Robust OFDM receivers for dispersive time-varying channels: equalization and channel acquisition. IEEE Transactions on Communications 2004, 52(4):572–583. 10.1109/TCOMM.2004.826354

    Article  Google Scholar 

  8. 8.

    Jeon WG, Chang KH, Cho YS: An equalization technique for orthogonal frequency-division multiplexing systems in time-variant multipath channels. IEEE Transactions on Communications 1999, 47: 27–32. 10.1109/26.747810

    Article  Google Scholar 

  9. 9.

    Rugini L, Banelli P, Leus G: Simple equalization of time-varying channels for OFDM. IEEE Communications Letters 2005, 9(7):619–621. 10.1109/LCOMM.2005.1461683

    Article  Google Scholar 

  10. 10.

    Schniter P: Low-complexity equalization of OFDM in doubly selective channels. IEEE Transactions on Signal Processing 2004, 52: 1002–1011. 10.1109/TSP.2004.823503

    MathSciNet  Article  Google Scholar 

  11. 11.

    Harris FJ: On the use of windows for harmonic analysis with the discrete Fourier transform. Proceedings of the IEEE 1978, 66(1):51–83.

    Article  Google Scholar 

  12. 12.

    Al-Dhahir N, Sayed AH: The finite-length multi-input multi-output MMSE-DFE. IEEE Transactions on Signal Processing 2000, 48(10):2921–2936. 10.1109/78.869048

    Article  Google Scholar 

  13. 13.

    Stamoulis A, Giannakis GB, Scaglione A: Block FIR decision-feedback equalizers for filterbank precoded transmissions with blind channel estimation capabilities. IEEE Transactions on Communications 2001, 49(1):69–83. 10.1109/26.898252

    Article  Google Scholar 

  14. 14.

    Kannu AP, Schniter P: MSE-optimal training for linear time-varying channels. Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '05), March 2005, Philadelphia, Pa, USA 3(1):789–792.

    Google Scholar 

  15. 15.

    Ma X, Giannakis GB, Ohno S: Optimal training for block transmissions over doubly-selective wireless fading channels. IEEE Transactions on Signal Processing 2003, 51(5):1351–1366. 10.1109/TSP.2003.810304

    MathSciNet  Article  Google Scholar 

  16. 16.

    Stamoulis A, Diggavi SN, Al-Dhahir N: Intercarrier interference in MIMO OFDM. IEEE Transactions on Signal Processing 2002, 50(10):2451–2464. 10.1109/TSP.2002.803347

    Article  Google Scholar 

  17. 17.

    Golub GH, Van Loan CF: Matrix Computations. 3rd edition. Johns Hopkins University Press, Baltimore, Md, USA; 1996.

    MATH  Google Scholar 

  18. 18.

    Tong L, Sadler BM, Dong M: Pilot-assisted wireless transmissions. IEEE Signal Processing Magazine 2004, 21(6):12–25. 10.1109/MSP.2004.1359139

    Article  Google Scholar 

  19. 19.

    Negi R, Cioffi J: Pilot tone selection for channel estimation in a mobile OFDM system. IEEE Transactions on Consumer Electronics 1998, 44(3):1122–1128. 10.1109/30.713244

    Article  Google Scholar 

  20. 20.

    Giannakis GB, Tepedelenlioglu C: Basis expansion models and diversity techniques for blind identification and equalization of time-varying channels. Proceedings of the IEEE 1998, 86(10):1969–1986. 10.1109/5.720248

    Article  Google Scholar 

  21. 21.

    Leus G, Moonen M: Equalization techniques for fading channels. In Handbook on Signal Processing for Communications. Edited by: Ibnkahla M. CRC Press, Boca Raton, Fla, USA; 2004. chapter 16

    Google Scholar 

  22. 22.

    Kay SM: Fundamentals of Statistical Signal Processing: Estimation Theory. Volume 1. Prentice Hall, Englewood Cliffs, NJ, USA; 1993.

    MATH  Google Scholar 

  23. 23.

    Zemen T, Mecklenbraäuker CF: Time-variant channel equalization via discrete prolate spheroidal sequences. Proceedings of the IEEE Asilomar Conference on Signals, Systems and Computers, November 2003, Pacific Grove, Calif, USA 2: 1288–1292.

    Google Scholar 

  24. 24.

    Borah DK, Hart BD: Frequency-selective fading channel estimation with a polynomial time-varying channel model. IEEE Transactions on Communications 1999, 47(6):862–873. 10.1109/26.771343

    Article  Google Scholar 

  25. 25.

    Leus G: On the estimation of rapidly time-varying channels. Proceedings of European Signal Processing Conference (EUSIPCO '04), September 2004, Vienna, Austria 2227–2230.

    Google Scholar 

  26. 26.

    Kannu AP, Schniter P: Capacity analysis of MMSE pilot patterns for doubly-selective channels. Proceedings of 6th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC '05), June 2005, New York, NY, USA

    Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Luca Rugini.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Rugini, L., Banelli, P. & Leus, G. Low-Complexity Banded Equalizers for OFDM Systems in Doppler Spread Channels. EURASIP J. Adv. Signal Process. 2006, 067404 (2006).

Download citation


  • Channel Estimation
  • OFDM System
  • Doppler Spread
  • Receiver Architecture
  • Basis Expansion Model