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
Link To Document :
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