SpringerLink
Log in

On Detection in MIMO-OFDM Systems Over Highly Mobile Wireless Channels

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

High mobility support of multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems plays a major role in wireless communication systems. Conventional detection approaches for MIMO-OFDM systems assume the channel is constant for at least one OFDM symbol duration. However, the time variation of the channel on account of mobility over an OFDM symbol period causes a loss of subchannel orthogonality which results in inter-carrier interference. In this paper, we propose the space alternating generalized expectation maximization (SAGE) based signal detection for MIMO-OFDM systems and compared by the zero forcing (ZF), minimum mean square error (MMSE), vertical Bell laboratories layered space-time (VBLAST) detection methods by considering complexity and performance tradeoffs. Simulation results show that the SAGE based detection has comparable performance with the VBLAST while needs lower computational complexity. It is also shown that both SAGE and VBLAST have a clear BER performance advantage over the MMSE and ZF detections. We also investigate the sensitivity of detection MIMO-OFDM signals to channel estimation errors by the application of a simple frequency domain based pilot based channel estimation. It is shown that the superiority of the SAGE scheme is also valid in the case of channel imperfections.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Li, Y., Winters, J., & Sollenberger, N. (2002). MIMO-OFDM for wireless communications: Signal detection with enhanced channel estimation. IEEE Transactions on Communications, 50(9), 1471–1477.

    Article  Google Scholar 

  2. Willink, T. (2005). MIMO-OFDM for broadband fixed wireless access. IEE Proceedings on Communications, 152(1), 75–81.

    Article  Google Scholar 

  3. Rossi, P., & Muller, R. (2008). Joint twofold-iterative channel estimation and multiuser detection for MIMO-OFDM systems. IEEE Transaction on Wireless Communications, 7(11 Part 2), 4719–4729.

    Article  Google Scholar 

  4. Glickenstein, H. (2009). High-speed trains [transportation systems]. Vehicular Technology Magazine IEEE, 4(4), 9–14.

    Article  Google Scholar 

  5. Li, Y., & Cimini, L. (2001). Bounds on the interchannel interference of OFDM in time-varying impairments. IEEE Transactions on Communications, 49(3), 401–404.

    Article  MATH  Google Scholar 

  6. Stamoulis, A., Diggavi, S. N., & Al-Dhahir, N. (2002). Intercarrier interference in MIMO-OFDM. IEEE Transaction on Signal Processing, 50(10), 2451–2464.

    Article  Google Scholar 

  7. Barhumi, I., Leus, G., & Moonen, M. (2006). Equalization for OFDM over doubly-selective channels. IEEE Transaction on Signal Processing, 54(4), 1445–1458.

    Article  MATH  Google Scholar 

  8. Huang, X., & Wu, H.-C. (2007). Robust and efficient intercarrier interference mitigation for OFDM systems in time-varying fading channels. IEEE Transactions on Vehicular Technology, 56(5), 2517–2528.

    Article  Google Scholar 

  9. Jeon, W. G., Chang, K. H., & Cho, Y. S. (1999). An equalization technique for orthogonal frequency-division multiplexing systems in time-variant multipath channels. IEEE Transactions on Communications, 47(1), 27–32.

    Article  Google Scholar 

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

    Article  Google Scholar 

  11. Schniter, P. (2004). Low-complexity equalization of OFDM in doubly-selective channels. IEEE Transactions on Signal Processing, 52(4), 1002–1011.

    Article  MathSciNet  Google Scholar 

  12. Rugini, L., Banelli, P., & Leus, G. (2006). Low-complexity banded equalizers for OFDM systems in Doppler spread channels. EURASIP Journal on Applied Signal Processing, 2006, 1–13.

    Article  Google Scholar 

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

    Article  Google Scholar 

  14. Tonello, A. (2002). Asynchronous multicarrier multiple access: Optimal and sub-optimal detection and decoding. Bell Labs Technical Journal, 7(3), 191–217.

    Article  Google Scholar 

  15. Choi, Y.-S., Voltz, P. J., & Cassara, F. A. (2001). On channel estimation and detection for multicarrier signals in fast and selective Rayleigh fading channels. IEEE Transactions on Communications, 49(8), 1375–1387.

    Article  MATH  Google Scholar 

  16. Tomasin, S., Gorokhov, A., Yang, H., & Linnartz, J.-P. (2005). Iterative interference cancellation and channel estimation for mobile OFDM. IEEE Transactions on Wireless Communications, 4(1), 238–245.

    Article  Google Scholar 

  17. Hou, S. W., & Ko, C. C. (2009). Intercarrier interference suppression for OFDMA uplink in time-and frequency-selective fading channels. IEEE Transactions on Vehicular Technology, 58(6), 2741–2754.

    Article  Google Scholar 

  18. Dogan, H., Panayirci, E., & Poor, H. V. (2010). Low-complexity joint data detection and channel equalisation for highly mobile orthogonal frequency division multiplexing systems. IET Communications, 4(8), 1000–1011.

    Article  MathSciNet  MATH  Google Scholar 

  19. Hsu, C. Y., & Wu, W. R. (2009). Low-complexity ICI mitigation methods for high-mobility SISO/MIMO-OFDM systems. IEEE Transactions on Vehicular Technology, 58(6), 2755–2768.

    Article  Google Scholar 

  20. Beheshti, M., Omidi, M., & Doost-Hoseini, A. (2010). Frequency-domain equalization for MIMO-OFDM over doubly selective channels. In 5th International symposium on telecommunications (IST), 2010 (pp. 431–436).

  21. Park, K.-W., & Cho, Y.-S. (2005). An MIMO-OFDM technique for high-speed mobile channels. IEEE Communications Letters, 9(7), 604–606.

    Article  Google Scholar 

  22. Zamiri-Jafarian, H., & Pasupathy, S. (2007). Robust and improved channel estimation algorithm for MIMO-OFDM systems. IEEE Transactions on Wireless Communications, 6(6), 2106–2113.

    Article  Google Scholar 

  23. Pirak, C., Wang, J., Liu, K., & Jitapunkul, S. (2006). Adaptive channel estimation using pilot-embedded data-bearing approach for MIMO-OFDM systems. IEEE Transactions on Signal Processing, 54(12), 4706–4716.

    Article  Google Scholar 

  24. Song, W.-G., & Lim, J.-T. (2006). Channel estimation and signal detection for MIMO-OFDM with time varying channels. IEEE Communications Letters, 10(7), 540–542.

    Google Scholar 

  25. Hardjawana, W., Li, R., Vucetic, B., Li, Y., & Yang, X. (2010). A new iterative channel estimation for high mobility MIMO-OFDM systems. In Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st (pp. 1–5).

  26. Yang, B., Cao, Z., & Letaief, K. B. (2001). Analysis of low-complexity windowed DFT-based MMSE channel estimator for OFDM systems. IEEE Transactions on Communications, 49(11), 1977–1987.

    Article  MATH  Google Scholar 

  27. Wu, Y., & Luo, H. (2008). Channel estimation for MIMO-OFDM systems in non-sample-spaced multipath channels. In Congress on Image and Signal Processing, 2008. CISP ’08 (Vol. 5, pp. 88–92).

  28. **e, Y., Li, Q., & Georghiades, C. N. (2007). On some near optimal low complexity detectors for MIMO fading channels. IEEE Transactions on Wireless Communication, 6(4), 1182–1186.

    Article  Google Scholar 

  29. Yalcin, M., Akan, A., & Dogan, H. (2012). Low-complexity channel estimation for OFDM systems in high mobility fading channels. Turkish Journal of Electrical Engineering and Computer Science, 20(4), 583–592.

    Google Scholar 

  30. Fessler, J., & Hero, A. (1994). Space-alternating generalized expectation-maximization algorithm. IEEE Transactions on Signal Processing, 42(10), 2664–2677.

    Article  Google Scholar 

  31. Dogan, H. (2008). EM/SAGE based ML channel estimation for uplink DS-CDMA systems over time-varying fading channels. IEEE Communications Letters, 12(10), 740–742.

    Article  Google Scholar 

  32. Barhumi, I., Leus, G., & Moonen, M. (2003). Optimal training design for MIMO-OFDM systems in mobile wireless channels. IEEE Transactions on Signal Processing, 51(6), 1615–1624.

    Article  Google Scholar 

  33. Ahmadi, S. (2010). Mobile WiMAX: A systems approach to understanding IEEE 802.16 m radio access technology. Waltham: Academic Press.

    Google Scholar 

  34. Patzold, M. (2003). Mobile fading channels. New Jersey: Wiley.

    Google Scholar 

  35. “3GPP TS 25.943 V6.0.0, Deployment aspects (Release 6),” 2004-12.

  36. Biglieri, E. (2005). Coding for wireless channels. New York: Springer.

    Google Scholar 

  37. Moiseev, S., Filin, S., Kondakov, M., Garmonov, A., & Savinkov, A. (Sept 2006). Practical propagation channel robust BLER estimation in the OFDM/TDMA and OFDMA broadband wireless access networks. In Vehicular Technology Conference, 2006. VTC-2006 Fall. 2006 IEEE 64th (pp. 1–5).

  38. Peng, W., Adachi, F., Ma, S., Wang, J., & Ng, T.-S. (Nov 2008). Effects of channel estimation errors on V-BLAST detection. In Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE (pp. 1–5).

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Istanbul University, Istanbul, Turkey

    Hakan Doğan

Authors
  1. Hakan Doğan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hakan Doğan.

Additional information

This work is supported in part by the Research Fund of the University of Istanbul. Project number: 45861.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Doğan, H. On Detection in MIMO-OFDM Systems Over Highly Mobile Wireless Channels. Wireless Pers Commun 86, 683–704 (2016). https://doi.org/10.1007/s11277-015-2952-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2952-7

Keywords

Search

Navigation