• DocumentCode
    2122602
  • Title

    A deterministic simulation modeling & analysis for the improvement of signal-to-noise ratio (SNR) based on ambient noise sources in underwater acoustic communication channel

  • Author

    Iqbal, H.N. ; Shaheen, Shadi ; Qazi, H. ; Iqbal, Jamshed

  • Author_Institution
    Centres of Excellence in Sci. & Appl. Technol. (CESAT), Islamabad, Pakistan
  • fYear
    2013
  • fDate
    15-19 Jan. 2013
  • Firstpage
    335
  • Lastpage
    338
  • Abstract
    This paper encompasses the sensitivity of SNR due to ambient noise sources individually using gradient method. The Gradient method has its own significance in the mathematical modeling and the purpose of using this method is of two fold; First, it gives the sensitivity of selected dependent variable with respect to the small and systematic changes in the independent variables separately or compositely in an equation. Second, it helps to determine a way to search for the optimal region or optimal values of the independent variables. Hence, this paper is intended to highlight the optimal region in order to determine a direction for the improvement of SNR in an underwater acoustic communication channel. In this paper, the gradient vectors of SNR have been modeled in MATLAB keeping in consideration the parameters as turbulence, shipping activities, wind and heat involved in underwater acoustic communication channel. The input model of SNR has been kept devoid of probability theory and uses some statistical approximations of underwater acoustic noise. Due to the absence of randomness in the variables of input model of SNR, the model output offers no uncertainties; hence giving a deterministic simulation model of the gradient vectors.
  • Keywords
    acoustic noise; gradient methods; underwater acoustic communication; MATLAB; ambient noise sources; deterministic simulation modeling; gradient method; gradient vectors; mathematical modeling; optimal region; probability theory; signal-to-noise ratio; underwater acoustic communication channel; underwater acoustic noise; Acoustics; Artificial neural networks; Computational modeling; Heating; Protocols; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Sciences and Technology (IBCAST), 2013 10th International Bhurban Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    978-1-4673-4425-8
  • Type

    conf

  • DOI
    10.1109/IBCAST.2013.6512174
  • Filename
    6512174