A Signal Processing Approach to Estimate Underwater Network Cardinalities with Lower Complexity

Hossain, S.A.; Mallik, A.; Arefin, Md. A.

doi:10.22061/jecei.2017.702

Document Type : Original Research Paper

Authors

¹ Department of Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, Bangladesh

² Department of Mechanical Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, Bangladesh

https://doi.org/10.22061/jecei.2017.702

Abstract

An inspection of signal processing approach in order to estimate underwater network cardinalities is conducted in this research. A matter of key prominence for underwater network is its cardinality estimation as the number of active cardinalities varies several times due to numerous natural and artificial reasons due to harsh underwater circumstances. So, a proper estimation technique is mandatory to continue an underwater network properly. To solve the problem, we used a statistical tool called cross-correlation technique, which is a significant aspect in signal processing approach. We have considered the mean of cross-correlation function (CCF) of the cardinalities as the estimation parameter in order to reduce the complexity compared to the former techniques. We have used a suitable acoustic signal called CHIRP signal for the estimation purpose which can ensure better performance for harsh underwater practical conditions. The process is shown for both two and three sensors cases. Finally, we have verified this proposed theory by a simulation in MATLAB programming environment.

Graphical Abstract

Keywords

20.1001.1.23223952.2017.5.2.5.5

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Journal of Electrical and Computer Engineering Innovations (JECEI)

A Signal Processing Approach to Estimate Underwater Network Cardinalities with Lower Complexity

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References

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Volume 5, Issue 2 - Serial Number 10
July 2017
Pages 131-138

A Signal Processing Approach to Estimate Underwater Network Cardinalities with Lower Complexity

References

References

Send comment about this article

Volume 5, Issue 2 - Serial Number 10July 2017Pages 131-138

Volume 5, Issue 2 - Serial Number 10
July 2017
Pages 131-138