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A modified ZF algorithm for signal detection in an underwater MIMO STBC-OFDM acoustic communication system

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Abstract

In this paper, we propose a novel signal detection algorithm to improve the performance of the multiple input multiple output (MIMO) space–time block code-orthogonal frequency-division multiplexing (STBC-OFDM) system in the underwater acoustic channel. Our special case for the underwater channel is the 114th station in the Caspian Sea. A model for an underwater MIMO-OFDM system is proposed first. Second, a signal coding method based on space–time block coding is employed. Finally, M-ZF, a modified signal detection algorithm, is then proposed for this system. Moreover, we compare M-ZF to ML, ZF, and MMSE. Another significant aspect of this paper is modeling an underwater acoustic channel using data from the Caspian Sea. In the modeling of the underwater channel, all actual conditions are considered. Ultimately, we evaluate the proposed algorithm in the underwater channel of the Caspian Sea. Simulation results demonstrate that the proposed algorithm has a lower time cost and superior bit error rate (BER) performance than others.

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References

  1. Sing AC, Nelson JK, Kozat SS (2009) Signal processing for underwater acoustic communications. IEEE Commun Mag 47(1):90–96

    Article  Google Scholar 

  2. Qiao G, Babar Z, Ma L, Liu S, Wu J (2017) MIMO-OFDM underwater acoustic communication systems_a review. Phys Commun 23:56–64

    Article  Google Scholar 

  3. Laufen T, Xu X (2017) Digital underwater acoustic communications, 1st edn. Academic, New York, NY, USA

    Google Scholar 

  4. Jiang R, Cao S, Xue C, Tang L (2017) Modeling and analyzing of underwater acoustic channels with curvilinear boundaries in shallow ocean. In: 2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, Xiamen, China, pp 1–6

  5. Etter PC (2018) Underwater acoustic modeling and simulation. CRC Press, Boca Raton, FL, USA

    Book  Google Scholar 

  6. Wang J, Kong D, Chen W (2017) Cooperative multiple-input multiple-output communication for underwater acoustic sensor networks. Period Ocean Univ China 47(9):126–133

    Google Scholar 

  7. Wang J, Wang Q, Zhu F, Chen W, Han Y (2017) An energy-efficient algorithm based on the tradeoff diversity and multiplexing of MIMO for underwater sensor networks. Microelectron Comput 34(3):136–140

    Google Scholar 

  8. Abdallah M (2012) MIMO/OFDM convex optimization applications. In: 2012 IEEE Long Island Systems, Applications and Technology Conference (LISAT). IEEE, Farmingdale, NY, pp 1–5

  9. Sampath H, Talwar S, Tellado J, Erceg V, Paulraj A (2002) A fourth-generation MIMO-OFDM broadband wireless system: design performance and field trial results. IEEE Commun Mag 40(9):143–149

    Article  Google Scholar 

  10. Kim S (2012) Angle-domain frequency-selective sparse channel estimation for underwater MIMO-OFDM systems. IEEE Commun Lett 16(5):685–687

    Article  Google Scholar 

  11. Chen P, Rong Y, Nordholm S, He Z, Duncan AJ (2017) Joint channel estimation and impulsive noise mitigation in underwater acoustic OFDM communication systems. IEEE Transac Wireless Commun 16(9):6165–6178

    Article  Google Scholar 

  12. Bocus MJ, Agrafiotis D, Doufexi A (2018) Underwater acoustic video transmission using MIMO-FBMC. In: 2018 OCEANS-MTS/IEEE Kobe Techno-Oceans (OTO). IEEE, Kobe, Japan, pp 1–6

  13. Zhou G, Li Y, He Y, Wang X, Yu M (2018) Artificial fish swarm based power allocation algorithm for MIMO-OFDM relay underwater acoustic communication. IET Commun 12(9):1079–1085

    Article  Google Scholar 

  14. Tu K, Duman TM, Proakis JG, Stojanovic M (2010) Cooperative MIMO-OFDM communications: receiver design for Doppler-distorted underwater acoustic channels. In: 2010 Conference record of the forty fourth asilomar conference on signals, systems and computers. IEEE, Pacific Grove, CA, pp 1335–1339

  15. Zhang L, Han J, Huang J, Zhang Q (2016) Iterative channel estimation and equalization for underwater acoustic MIMO SFBC OFDM communication. In: 2016 IEEE/OES China Ocean Acoustics (COA). IEEE, Harbin, China, pp 1–6

  16. Zhou Y, Tong F (2019) Research and development of a highly reconfigurable OFDM MODEM for shallow water acoustic communication. IEEE Access 7:123569–123582

  17. Nassiri M, Baghersalimi G (2018) Comparative performance assessment between FFT-based and FRFT-based MIMO OFDM systems in underwater acoustic communications. IET Commun 12(6):719–726

    Article  Google Scholar 

  18. Liu B, Jia N, Huang J, Guo S, Xiao D, Ma Li (2022) Autoregressive model of an underwater acoustic channel in the frequency domain. Appl Acoust 185:108397

    Article  Google Scholar 

  19. Zhang Y, Wang H, Li C, Chen X, Meriaudeau F (2022) On the performance of deep neural network aided channel estimation for underwater acoustic OFDM communications. Ocean Eng 259:111518

    Article  Google Scholar 

  20. Onasami O, Feng M, Xu H, Haile M, Qian L (2022) Underwater acoustic communication channel modeling using reservoir computing. IEEE Access 10:56550–56563

  21. Wilson W (1960) Equation for the speed of sound in sea water. J Acoust Soc Amer 32(10):1357

    Article  Google Scholar 

  22. Grosso VAD (1974) New equation for the speed of sound in natural waters (with Comparison to Other Equations). J Acoust Soc Amer 56(4):1084–1091

    Article  Google Scholar 

  23. Clay C, Medwin H (1977) Acoustical oceanography: principals and applications. John Wiley & Sons, New York, NY

    Google Scholar 

  24. Brekhovskikh LM, Lysanov YP, Lysanov JP (2003) Fundamentals of ocean acoustics. Springer Science & Business Media.

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Authors and Affiliations

  1. Babol Noshirvani University of Technology, Babol, Iran

    Mohammad Akhondi

  2. North Research Center for Science & Technology, Malek Ashtar University of Technology, Mazandaran, Iran

    Mohammad Ali Alirezapouri

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  1. Mohammad Akhondi
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  2. Mohammad Ali Alirezapouri
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Correspondence to Mohammad Akhondi.

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Akhondi, M., Alirezapouri, M.A. A modified ZF algorithm for signal detection in an underwater MIMO STBC-OFDM acoustic communication system. Ann. Telecommun. 78, 491–507 (2023). https://doi.org/10.1007/s12243-023-00945-y

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  • DOI: https://doi.org/10.1007/s12243-023-00945-y

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