Journal of Communication Engineering

Journal of Communication Engineering

Complete Performance Analysis of Underwater VLC Diffusion Adaptive Networks

Document Type : Research Paper

Authors
Hosein Abdavinejad 1
Hadi Baghali 1
Javad Ostadieh 2
Ehsan Mostafapour 3
Changiz Ghobadi 4
Javad Nourinia 4
1 Dept. electrical engineering, Urmia University, Urmia, Iran.
2 Department of electrical engineering, Urmia University, Urmia, Iran.
3 Urmia University
4 Department of Electrical and Computer Engineering Urmia University, Urmia, Iran
10.22070/jce.2021.13681.1179
Abstract
In this paper, we simulated a diffusion adaptive network in the underwater environment. The communication method between the nodes of this network is assumed to be the visible light communication technology (VLC) which in the underwater condition is known as the UVLC. The links between the nodes in this case are contaminated with the optical noise and turbulence. These contaminations are modeled with the proper statistical distributions depending on the underwater conditions. The optical turbulence modeling link coefficients are shown to be following the Log-normal distribution which its mean and variance are directly dependent on the temperature and the salinity of the simulated water and the assumed distance between the diffusion network nodes. The performance of the diffusion network in using UVLC technology is then analyzed both with simulations and theoretical calculations and the results are presented using the steady-state error metrics. Our analysis showed that the diffusion network can be implemented underwater with the VLC technology providing that the distance between the network nodes is less than 10 meters. Also, in order to guarantee the convergence of the adaptive network, the water salinity level and temperature must not exceed the values that are presented in our simulations.
Keywords
Diffusion adaptation
Visible light communication
Underwater
Optical turbulence
Log-normal distribution
Convergence
Steady-State
  1. C. M. Gussen, P. S. Diniz, M. L. Campos, W. A. Martins, F. M. Costa, and J. N. Gois, “A survey of underwater wireless communication technologies,” Journal. Commun. Inf. Sys., vol. 31, no. 1, pp. 242-255, Oct. 2016.
  2. Z. Zeng, S. Fu, H. Zhang, Y. Dong, and J. Cheng, “A survey of underwater optical wireless communications,” IEEE Comm. Surveys Tuts., vol. 19, no. 1, pp. 204-238, Oct. 2017.
  3. D. C. Sigee, Freshwater microbiology: biodiversity and dynamic interactions of microorganisms in the aquatic environment, John Wiley & Sons, 2005.
  4. A. P. Klimley, The biology of sharks and rays, University of Chicago Press, 2013.
  5. C. Wang, H. Y. Yu, Y. J. Zhu and T. Wang, "Blind detection for SPAD-based underwater VLC system under P–G mixed noise model," IEEE Commun. Lett., vol. 21, no. 12, pp. 2602-2605, Dec. 2017.
  6. A. Tabeshnezhad and M. A. Pourmina, "Outage analysis of relay-assisted underwater wireless optical communication systems", Opt. Commun., vol. 405, pp. 297-305, Dec. 2017.
  7. T. Shafique, O. Amin, M. Abdallah, I. S. Ansari, M. S. Alouini and K. Qaraqe, “Performance analysis of single-photon avalanche diode underwater VLC system using ARQ,” IEEE Photonic Journal, vol. 9, no. 5, pp. 1-11, Oct. 2017.
  8. S. Hessien, S. Tokgöz, N. Anous, A. Boyacı, M. Abdallah, K. Qaraqe, “Experimental evaluation of OFDM-based underwater visible light communication system,” IEEE Photonic Journal, vol. 10, no. 5, pp. 1-13, Oct. 2018.
  9. E. Mostafapour, Ch. Ghobadi, M.C. Amirani, “Non-stationary channel estimation with diffusion adaptation strategies over distributed networks,” Wireless Pers. Commun., vol. 99, no. 3, pp. 1377-1390, Dec. 2018.
  10. A. Khalili, A. Rastegarnia and S. Sanei, ‘Performance analysis of incremental LMS over flat fading channels,” IEEE Trans. Control Netw. Syst., vol. 99: 1-11, Jan. 2016.
  11. A. Abdolee, B. Champagne and A. H. Sayed, “Diffusion LMS strategies for parameter estimation over fading wireless channels,” IEEE Intern. Conf. on Communications, pp. 1926–1930, June 2013.
  12. A. Khalili, M.A. Tinati, A. Rastegarnia, and J.A. Chambers, “Steady state analysis of diffusion LMS adaptive networks with noisy links,” IEEE Trans. Signal Process. vol. 60: 974–979, Oct. 2012.
  13. A. Aminfar, Ch. Ghobadi, M. Chehel Amirani, “Convergence analysis of diffusion adaptive networks through free space optical communication channels,” Wireless Pers. Commun., vol. 107, no. 2, pp. 1199-1218, April 2019.
  14. A. H. Sayed and F. Cattivelli, “Distributed adaptive learning mechanisms,” in Handbook Array Process. Sens. Networks, S. Haykin and K. J. Ray Liu, Eds. Wiley, pp. 693–722, 2009.
  15. M. Elamassie, M. Uysal, “Performance characterization of vertical underwater VLC links in the presence of turbulence,” 11th Intern. Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), Hungary, July 2018.
  16. Noha Anous, M. Abdallah, M. Uysal, K. Qaraqe, “Performance evaluation of LOS and NLOS vertical inhomogeneous links in underwater visible light communications,” IEEE Access, vol. 8, pp. 22408-22420, March 2018.
  17. I. Sahnoun, I. S. Ansari, M. Abdellah, K. Qaraqe, “Performance analysis of adaptive modulation in underwater visible light communication,” 25th Intern. Conf. on Software, Telecommunication and Computer Networks (SOFTCOM), Croatia, Sept, 2017.
  18. H. Makine Oubei, R. T. Elafandy, T. K. Ng, M. Alouini, B. S. Ooi, “Performance evaluation of underwater wireless optical communications links in the presence of different air bubble populations,” IEEE Photonic Journal, vol. 9, no. 2, April 2017.
  19. M. Elamassie, S. M. Sait, and M. Uysal, “Underwater visible light communications in cascaded Gamma-Gamma turbulence,” 8th IEEE Globecom Workshop on Optical Wireless Communications (GC’18 WS - OWC), Abu Dhabi, United Arab Emirates, Dec. 2018.
  20. A. Aminfar, Ch. Ghobadi, M. Chehel Amirani, “Diffusion adaptation through free space optical (FSO) wireless communication channels,” IEEE 4th Intern. Conf. on Knowledge-Based Engineering and Innovation (KBEI-2017), Tehran, Iran, Dec. 2017.
  21. H. Abdi, C. Ghobadi, J. Nourinia, and A. Aminfar “Incremental adaptive networks working through FSO Log-normal turbulence channels,” The first west Asian colloquium on optical wireless communications, Isfahan, Iran, April 2018.
  22. A. Aminfar, M. Chehel Amirani, Ch. Ghobadi, “Incremental adaptive networks implemented by free space optical (FSO) communication,” Journal of Communication Engineering (JCE), vol. 7, no. 2, pp. 12-28, Summer and Autumn 2018.
  23. M. Jamali, A. Mirani, A. Parsay, B. Abolhassani, P. Nabavi, A. Chizari, P. Khorramshahi, S. Abdollahramezani and J. Salehi, "Statistical studies of fading in underwater wireless optical channels in the presence of air bubble, temperature, and salinity random variations," IEEE Trans. Commun., vol. 66, no. 10, pp. 4706-4723, Oct. 2018.
  24. M. Bernotas and C. Nelson, "Probability density function analysis for optimization of underwater optical communications systems," OCEANS 2015 - MTS/IEEE Washington, Washington DC, Oct. 2015.
  25. M. Cheng, L. Guo, and Y. Zhang, “Scintillation and aperture averaging for gaussian beams through non-kolmogorov maritime atmospheric turbulence channels,” Opt. Express, vol. 23, no. 25, pp. 32 606–32 621, Dec. 2015.
  26. M. Elamassie, M. Uysal, Y. Baykal, M. Abdallah, and K. Qaraqe, “Effect of eddy diffusivity ratio on underwater optical scintillation index,” J. Opt. Soc. Am. A, vol. 34, no. 11, pp. 1969–1973, Oct. 2017.
  27. S. Tannaz, Ch. Ghobadi, J. Nourinia and E. Mostafapour, “The node distance effects on the performance of the underwater VLC incremental adaptive networks,” Journa of modern optics, vol. 66, no. 21, pp. 2093-2098, Nov. 2019.
  28. J. Wang, S. Tannaz, C. Cai, A. Aliabadi, E. Mostafapour, and W. Zhang, “Performance analysis of wireless adaptive incremental networks under strong FSO link turbulence conditions,” IEEE ACCESS, vol. 8, pp. 12290–12299, Dec. 2019.
  29. S. Tannaz, C.Ghobadi; J. Nourinia, “Impacts of the Negative-exponential and the K-distribution modeled FSO turbulent links on the theoretical and simulated performance of the distributed diffusion networks,” Journal of Communication Engineering (JCE), vol. 8, no. 2, pp. 234-248, Summer and Autumn 2019.
  30. E. Mostafapour; M. Chehel Amirani; Ch. Ghobadi, J. Nourinia “Tracking performance of incremental LMS algorithm over adaptive distributed sensor networks,” Journal of Communication Engineering (JCE), vol. 4, no. 1, pp. 55-66, Winter and Spring 2015.