It is often essential to estimate the number of operating nodes in a wireless communication network (WCN), in which the nodes are deployed in different forms to cover small or large areas for a wide range of personal, scientific and commercial applications. The number of nodes may vary due to ad-hoc nature, power failure of nodes, or environmental disaster. In any communication network, it is important to estimate the number of nodes at any point in time for proper network operation and maintenance. Counting the number is very important for data collection, network maintenance and node localization. Also network performance depends on the area node ratio i.e. the number of operating nodes per unit area. Many estimation techniques are used to count the number of nodes in wireless communication networks, but in underwater environment they are not efficient. In this paper a cross-correlation based statistical signal processing approach for node estimation in underwater wireless communication network is proposed. In this method nodes are considered as acoustic signal sources and their number is calculated through the crosscorrelation of the acoustic signals received at two sensors placed in the network. The mean of the cross-correlation function is used as the estimation parameter in this process. Theoretical and simulation results are provided which justify the effectiveness of the proposed approach
