Srija Chowdhury

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Estimation of the number of nodes in a communication network is very important, particularly in ad hoc networks. But it is difficult to estimate in underwater wireless sensor networks due to long propagation delay, high absorption, and dispersion. Cross-correlation, a statistical signal processing approach is applied for this purpose, which is suitable for(More)
Cardinality estimation of underwater network is somewhat troublesome using terrestrial node estimation methods due to unique characteristics of underwater environment such as large propagation latency, node mobility, non-negligible capture effect, and high error rate. For this reason, a cardinality estimation method based on cross-correlation of Gaussian(More)
Bandwidth is the most monumental topic both for the terrestrial and underwater communications. For proper network operation the estimation of number of signal sources (N) is very important. Most of the protocol based techniques are failed to give the desired results of node estimation due to underwater properties (long propagation delay, high absorptions(More)
Due to the harshness of underwater environment, size estimation of underwater network is difficult using conventional protocol techniques. A statistical signal processing approach of size estimation is proposed for this purpose using cross-correlation of Gaussian signals, which is effective for any environment networks. Limited bandwidth of underwater(More)
Signal length possesses a very important role in size estimation of underwater wireless sensor network (UWSN). As size estimation is very tough in UWSN<sub>s</sub> using conventional protocol techniques, a cross-correlation based technique is introduced to estimate the number of nodes. In UWSN, The greater the signal length, the more energy is required to(More)
Network cardinality is very crucial factor to ensure proper functionality of a network. Because of inimitable properties of underwater environment (such as strong background noise, unavoidable capture effect, limited bandwidth, long propagation delay, high path loss, node mobility etc.) network cardinality estimation of underwater environment could be a(More)
It is very difficult to estimate the number and location of the operational nodes in underwater network using conventional protocol based techniques due to long propagation delay, strong background noise, non-negligible capture effect, high absorption and dispersion of underwater environment. So, a unique approach based on cross-correlation is applied for(More)
Transmit energy is a very important performance indicator of network cardinality estimation techniques. It is more significant for underwater networks as battery lifetime of nodes depend on it. To overcome the difficulty of underwater network cardinality estimation (in presence of large propagation latency, high error rate, node mobility, non-negligible(More)
In underwater network, it is very important to know the location of unmanned underwater vehicle (UUV). The unknown position of UUV considered as an unknown node that can be determined from the known node locations through underwater acoustic network. The known node locations considered here as fixed positioned node. The range data is measured between(More)