Skip to main content
Log in

Time-Varying Channel Equalization in Underwater Acoustic OFDM Communication System

  • Published:
Radioelectronics and Communications Systems Aims and scope Submit manuscript

Abstract

In this paper, three time-varying channel equalization schemes are studied in the underwater acoustic (UWA) Orthogonal Frequency Division Multiplexing (OFDM) communication system. The equalization algorithms are the zero-forcing (ZF) equalization algorithm, and the minimum mean square error equalization (MMSE) algorithm and the serial interference cancellation (SIC) equalization algorithm. Among the schemes, there is a problem of needing a large amount of operation when obtaining the inversion of the channel matrix. Then, to reduce the computation complexity of channel matrix inversion, the band approximation of the channel matrix, the serial equalization and the LDLH decomposition are also studied. To evaluate the efficacy of the algorithms studied in this paper, numerical simulation and the field experiment are both conducted. The simulation results proof that each equalization algorithm can work appropriately under different time-varying conditions, and valid the reliability of each simplified algorithm under the same Doppler factor. The results of two sets of field experiment also prove that the simplified algorithm eliminates the influence of the residual narrow band Doppler to a certain extent, and a better effect is obtained while a channel estimation algorithm with higher accuracy is combined.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

Similar content being viewed by others

References

  1. M. K. Tsatsanis, G. B. Giannakis, "Adaptive methods for equalization of rapidly fading channels," in Proceedings of MILCOM ’93 - IEEE Military Communications Conference (IEEE). DOI: https://doi.org/10.1109/MILCOM.1993.408590.

    Chapter  Google Scholar 

  2. I. Barhumi, G. Leus, M. Moonen, "Estimation and direct equalization of doubly selective channels," EURASIP J. Adv. Signal Process., v.2006, n.1, p.062831 (2006). DOI: https://doi.org/10.1155/ASP/2006/62831.

    Article  MATH  Google Scholar 

  3. S. Tomasin, A. Gorokhov, Haibing Yang, J.-P. Linnartz, "Iterative interference cancellation and channel estimation for mobile OFDM," IEEE Trans. Wirel. Commun., v.4, n.1, p.238 (2005). DOI: https://doi.org/10.1109/TWC.2004.840194.

    Article  Google Scholar 

  4. K. A. D. Teo, S. Ohno, "Optimal MMSE finite parameter model for doubly-selective channels," in GLOBECOM ’05. IEEE Global Telecommunications Conference, 2005 (IEEE). DOI: https://doi.org/10.1109/GLOCOM.2005.1578424.

    Chapter  Google Scholar 

  5. T. Zemen, C. F. Mecklenbrauker, "Time-variant channel estimation using discrete prolate spheroidal sequences," IEEE Trans. Signal Process., v.53, n.9, p.3597 (2005). DOI: https://doi.org/10.1109/TSP.2005.853104.

    Article  MathSciNet  MATH  Google Scholar 

  6. G. Taubock, F. Hlawatsch, "A compressed sensing technique for OFDM channel estimation in mobile environments: Exploiting channel sparsity for reducing pilots," in 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE). DOI: https://doi.org/10.1109/ICASSP.2008.4518252.

    Chapter  Google Scholar 

  7. J. Jin, Y. Gu, S. Mei, "An introduction to compressive sampling and its applications," J. Electron. Inf. Technol., v.32, n.2, p.470 (2010). DOI: https://doi.org/10.3724/SP.J.1146.2009.00497.

    Article  Google Scholar 

  8. Y. Zhou, Y. Wu, D. Chen, F. Tong, "Compressed sensing estimation of underwater acoustic MIMO channels based on temporal joint sparse recovery," Dianzi Yu Xinxi Xuebao/Journal Electron. Inf. Technol., v.38, n.8, p.1920 (2016). DOI: https://doi.org/10.11999/JEIT151158.

    Article  Google Scholar 

  9. H. Huang, W. Su, X. Jiang, "An improved compressed sensing reconstruction algorithm used in sparse channel estimation," in 2016 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) (IEEE). DOI: https://doi.org/10.1109/ICSPCC.2016.7753737.

    Chapter  Google Scholar 

  10. L. Jing, C. He, L. Zhang, Q. Meng, J. Huang, Q. Zhang, "Iterative block decision feedback equalizer with soft detection for underwater acoustic channels," Dianzi Yu Xinxi Xuebao/Journal Electron. Inf. Technol., v.38, n.4, p.885 (2016). DOI: https://doi.org/10.11999/JEIT150669.

    Article  Google Scholar 

  11. Y. Xie, L. Zhou, J. Liu, "Linearly time-varying channel estimation method with ICI mitigation for OFDM systems," Inf. Technol., n.1, p.67 (2018). DOI: https://doi.org/10.13274/j.cnki.hdzj.2018.01.016.

    Article  Google Scholar 

  12. J. Zhao, K. Huo, Y. Liu, X. Yang, "Cyclic prefix based phase-coded OFDM radar Doppler offset estimation and compensation," Dianzi Yu Xinxi Xuebao/Journal Electron. Inf. Technol., v.39, n.4, p.938 (2017). DOI: https://doi.org/10.11999/JEIT160549.

    Article  Google Scholar 

  13. S. Sarowa, H. Singh, S. Agrawal, B. S. Sohi, "A novel energy-efficient ICI cancellation technique for bandwidth improvements through cyclic prefix reuse in an OFDM system," Front. Inf. Technol. Electron. Eng., v.18, n.11, p.1892 (2017). DOI: https://doi.org/10.1631/FITEE.1601333.

    Article  Google Scholar 

  14. T. Hrycak, G. Matz, "Low-complexity time-domain ICI equalization for OFDM communications over rapidly varying channels," in 2006 Fortieth Asilomar Conference on Signals, Systems and Computers (IEEE). DOI: https://doi.org/10.1109/ACSSC.2006.355065.

    Chapter  Google Scholar 

  15. J. Huang, J. Huang, C. R. Berger, S. Zhou, P. Willett, "Iterative sparse channel estimation and decoding for underwater MIMO-OFDM," EURASIP J. Adv. Signal Process., v.2010, n.1, p.460379 (2010). DOI: https://doi.org/10.1155/2010/460379.

    Article  Google Scholar 

  16. L. Rugini, P. Banelli, G. Leus, "Simple equalization of time-varying channels for OFDM," IEEE Commun. Lett., v.9, n.7, p.619 (2005). DOI: https://doi.org/10.1109/LCOMM.2005.1461683.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anfu Zhu.

Ethics declarations

ADDITIONAL INFORMATION

Anfu Zhu

The author declares that he has no conflict of interest.

The initial version of this paper in Russian is published in the journal “Izvestiya Vysshikh Uchebnykh Zavedenii. Radioelektronika,” ISSN 2307-6011 (Online), ISSN 0021-3470 (Print) on the link http://radio.kpi.ua/article/view/S0021347020080038 with DOI: https://doi.org/10.20535/S0021347020080038

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, A. Time-Varying Channel Equalization in Underwater Acoustic OFDM Communication System. Radioelectron.Commun.Syst. 63, 405–417 (2020). https://doi.org/10.3103/S0735272720080038

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0735272720080038

Navigation