Underwater Acoustic Channel and Network Optimization

The objectives of this work are (1) to develop methods for acoustic channel prediction from nominal oceanographic data, and (2) to optimally design underwater acoustic networks to maximize the network surveillance performance, while minimizing its power consimption. The example network consists of a master node and a multitude of possibly mobile sensor nodes whose task is to report the information collected to the master node by relaying it from node to node. Acoustic channel characterization involves signal strngth prediction based on the transmossion loss; multipath intensity profile prediction based on acoustic propagation modeling, and prediction of Doppler spectrum due to random fluctuations using statistical characterization of surface scattering and nodes' spatial properties. In addition, adaptive channel estimation and interference prediction methods will be developed. Network design encompasses optimal dynamic routing and the choice of a multiple-access technique. It includes optimization of the network layout based on the acoustic channel prediction; network initialization procedure; data frame design; multiple-access technique optimization based on capacity calculations, and optimization of routing functions. Dynamic routing algorithm design provides adaptive selection of optimal routes based on the channel state, as well as flexibility to node failures and new node initializations. Acoustic channel characterization involves signal strngth prediction based on the transmossion loss; multipath intensity profile prediction based on acoustic propagation modeling, and prediction of Doppler spectrum due to random fluctuations using statist Network design encompasses optimal dynamic routing and the choice of a multiple-access technique. It includes optimization of the network layout based on the acoustic channel prediction; network initialization procedure; data frame design; multiple-access