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Theoretical Analysis of the Underwater Incremental Adaptive Network Performance Based on the VLC Technology

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Abstract

In this paper, the underwater implementation of the incremental adaptive networks is proposed based on the visible light communication technology. The underwater distance between transmitter and receiver nodes and the salinity and temperature levels of the considered water determines the stochastical properties of the underwater link that is modeled with the Log-normal distribution. The incremental network performance can be expressed with the excess mean square error and mean square deviation values and we used them in this paper for our theoretical analysis. Our findings showed that the distances between the nodes must not be more than 10 m or the incremental network will diverge from its estimation goal. The network performance is analyzed through multiple link distances and the results are presented with several simulations. The simulation results are devised in order to elaborate the effects of the underwater turbulent links on the performances of estimating adaptive network. Also, the impacts of different salinity and temperature levels are analyzed theoretically and the results are compared with the simulation results.

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References

  1. Elamassie, M., & Uysal M. (2018) Performance characterization of vertical underwater VLC links in the presence of turbulence. In 11th international symposium on communication systems, networks and digital signal processing (CSNDSP), Hungary.

  2. Elamassie, M., Sait, S. M., & Uysal, M. (2018). Underwater visible light communications in cascaded Gamma-Gamma Turbulence. In IEEE globecom workshops (GC Wkshps), United Arab Emirates.

  3. Morozs, N., Mitchell, P., & Zakharov, Y. (2018). Unsynchronized dual-hop scheduling for practical data gathering in underwater sensor networks. In IEEE forth underwater communications and networking conference (UComms), Italy.

  4. Heidemann, J., Stojanovic, M., & Zorzi, M. (2011). Underwater sensor networks: Applications, advances, and challenges. Philosophical Transactions of the Royal Society of London A: Mathematical, physical and engineering sciences,370(1958), 158–175.

    Article  Google Scholar 

  5. Ma, X., Yang, F., Liu, S., & Song, J. (2018). Novel compressive sensing based channel estimation for wideband underwater visible light communication. In IEEE international conference on communications (ICC), USA.

  6. Akram, M. S. M., Aravinda, L. G. D., Munaweera, M. K. P. D., Godaliyadda, G. M. R. I.& Ekanayake, M. P. B. (2017). Camera based visible light communication system for underwater applications. In IEEE international conference on industrial and information systems (ICIIS), USA.

  7. Amantayeva, A., Yerzhanova, M., Kizilirmak, R. C. (2018). Multiuser MIMO for underwater visible light communication. In IEEE international conference on computing and network communications (CoCoNet), Astana, Kazakhstanpp.

  8. Narmanlioglu, O., Kizilirmak, R. C., Miramirkhani, F., & Uysal, M. (2017). Cooperative visible light communications with full-duplex relaying. IEEE Photonics Journal,9(3), 1–7.

    Article  Google Scholar 

  9. Wang, F., Liu, Y., Jiang, F., & Chi, N. (2018). High speed underwater visible light communication system based on LED employing maximum ratio combination with multi-PIN reception. Optics Communications,425, 106–112.

    Article  Google Scholar 

  10. Zou, P., Liu, Y., Wang, F., Hu, F., & Chi, N. (2019). Enhanced performance of odd order square geometrical shaping QAM constellation in underwater and free space VLC system. Optics Communications,438, 132–140.

    Article  Google Scholar 

  11. Jamali, M., Mirani, A., Parsay, A., Abolhassani, B., Nabavi, P., Chizari, A., et al. (2018). Statistical studies of fading in underwater wireless optical channels in the presence of air bubble, temperature, and salinity random variations. IEEE Transactions on Communications,66(10), 4706–4723.

    Google Scholar 

  12. Khalili, A., Rastegarnia, A., & Sanei, S. (2016). Performance analysis of incremental LMS over flat fading channels. The IEEE Transactions on Control of Network Systems,99, 1–11.

    MATH  Google Scholar 

  13. Lopes, C. G., & Sayed, A. H. (2007). Incremental adaptive strategies over distributed networks. The IEEE Transactions on Signal Processing,55, 4064–4077.

    Article  MathSciNet  Google Scholar 

  14. Sayed, A. H., & Cattivelli, F. (2009). Distributed adaptive learning mechanisms. In S. Haykin & K. J. Ray Liu (Eds.), Handbook on array processing and sensor networks (pp. 693–722). London: Wiley.

    Google Scholar 

  15. Rastegarnia, A., Tinati, M. A., & Khalili, A. (2011). Steady-state analysis of incremental LMS adaptive networks with noisy links. The IEEE Transactions on Signal Processing,59(5), 2416–2421.

    Article  MathSciNet  Google Scholar 

  16. Ghassemlooy, Z., Popoola, W., & Rajbhandari, S. (2013). Optical wireless communications system and channel modeling with MATLAB. New York: CRC Press.

    Google Scholar 

  17. Uysal, M., Capsoni, C., Ghassemlooy, Z., Boucouvalas, A. C., & Udvary, E. G. (Eds.). (2016). Optical wireless communications: An emerging technology. Berlin: Springer.

    Google Scholar 

  18. Ghassemlooy, Z., Popoola, W., & Rajbhandari, S. (2017). Visible light communications theory and applications. New York: CRC Press.

    Book  Google Scholar 

  19. Abdi, H et al. (2018). Incremental adaptive networks working through FSO Log-normal turbulence channels. In The first west Asian colloquium on optical wireless communications, Isfahan, Iran.

  20. Aminfar, A., Chehel Amirani, M., & Ghobadi, Ch. (2018). Incremental adaptive networks implemented by free space optical (FSO) communication. Journal of communication engineering,7(2), 12–28.

    Google Scholar 

  21. Tannaz, S., Ghobadi, C., Nourinia, J., & Mostafapor E. (2018). The effects of negative exponential and k-distribution modeled FSO links on the performance of diffusion adaptive networks. In 9th international symposium on telecommunications (IST’2018), Tehran, Iran.

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Correspondence to Ehsan Mostafapour.

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Tannaz, S., Ghobadi, C., Nourinia, J. et al. Theoretical Analysis of the Underwater Incremental Adaptive Network Performance Based on the VLC Technology. Wireless Pers Commun 113, 17–32 (2020). https://doi.org/10.1007/s11277-020-07176-7

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  • DOI: https://doi.org/10.1007/s11277-020-07176-7

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