Performance Evaluation of Cross Correlation Based Node Estimation Technique

Estimating the number of operating nodes is an important factor in wireless communication network (WCN) in which the nodes are deployed in different forms to cover small or large areas of interest for a wide range of personal, scientific and commercial applications. It is important to estimate the number of operating nodes at any point in time for proper network operation and maintenance. Proper operation of a network depends on the total number of nodes present at a particular moment. Counting the number is very important in useful data collection, node localization and network maintenance. Also network performance depends on the area node ratio i.e. the number of operating nodes per unit area. So, node estimation is a vital requirement in wireless sensor network. At present, different estimation techniques exist but they are only effective for communication friendly networks. In underwater wireless sensor network node estimation faces a great difficulty due to underwater propagation characteristics such as high propagation delay, high absorption and dispersion. In such environment the number of nodes may vary frequently due to ad-hoc nature, power failure of nodes or environmental disaster. A statistical signal processing approach of node estimation is proposed in this paper and the performance of the proposed method is evaluated by comparing the results with other techniques. The nodes are considered as acoustic signal sources and their number is obtained through the cross correlation of the acoustic signals received at two sensors in the network. The mean of the cross correlation function is related with the number of nodes and is used as the estimation parameter in the process. Theoretical and simulation results are provided which show effectiveness of the signal processing approach instead of protocols in node estimation process.