TY - JOUR
ID - 702
TI - A Signal Processing Approach to Estimate Underwater Network Cardinalities with Lower Complexity
JO - Journal of Electrical and Computer Engineering Innovations (JECEI)
JA - JECEI
LA - en
SN - 2322-3952
AU - Hossain, S.A.
AU - Mallik, A.
AU - Arefin, Md. A.
AD - Department of Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, Bangladesh
AD - Department of Mechanical Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, Bangladesh
Y1 - 2017
PY - 2017
VL - 5
IS - 2
SP - 131
EP - 138
KW - Bins
KW - CHIRP signal
KW - Cross-correlation
KW - Underwater network cardinality (Node)
KW - Mean
DO - 10.22061/jecei.2017.702
N2 - 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.
UR - http://jecei.sru.ac.ir/article_702.html
L1 - http://jecei.sru.ac.ir/article_702_85f5bdea0ad6a5d5bfbf55ef723d2709.pdf
ER -