The formation and propagation of acoustic vortex waves have been of increasing interest for multiple applications, namely, underwater acoustic communications. Several methods have been presented to form these vortices in underwater environments; however, their performance and propagation over long distances is largely unstudied. Understanding the long-distance propagation of these waves is vital to enhancing their usefulness as an added degree of freedom in underwater acoustic communications systems. In this work, the ray tracing algorithm of bellhop is used to investigate the design parameters of vortex wave transducer and receiver arrays consisting of multiple rings of independently controlled transducers and simulate their performance.

Underwater acoustic system performance depends on several complex and dynamic environmental parameters, and simulating such performance is vital to the success of development and implementation of these systems. Because of the complexity of the environment and governing physical equations, realistic simulations can become computationally prohibitive. This is especially true of for large environments with many active systems being assessed. By utilizing convolutional neural networks (CNNs) trained on data generated by well-established physics based models (such as BELLHOP’s ray tracing algorithm), network predictions can be used lieu of physics-based models to significantly reduce the computational burden in the loop for system performance simulations. In this paper, the usefulness and limitations of using CNNs to estimate transmission loss (TL), which is a key element in determining system performance, is explored. Using BELLHOP’s ray tracing algorithm as a baseline, CNN’s were able to produce TL results with significantly lower errors than those estimates made using other estimation methods such as spherical spreading and K-nearest neighbors. This indicates that the computational costs of large underwater acoustic simulations may be shifted from inside the simulation to network training, thus allowing for more efficient traditional and Monte Carlo style simulations.

The underwater acoustic communications environment is severely band-limited, which leads to a bottleneck in data transfer. Existing methods of data transfer in underwater acoustic communications applications typically rely primarily on conventional temporal and frequency modulation techniques and achieve bit rates peaking at approximately 40 kb/s. One method of easing the bottleneck and increasing the data rate is to explore further potential degrees of freedom which may be utilized. Acoustic orbital angular momentum (OAM) is a physical quantity that characterizes the rotation in a propagating helical pressure wavefront. The unique phase patterns of OAM carrying vortex waves form an orthogonal basis which may be useful as an additional degree of freedom in acoustics communications applications; however, the long-distance propagation of these waves is largely unstudied. By employing BELLHOP’s ray tracing algorithm, the dominant features of a propagating OAM carrying vortex wave are tracked over long ranges (to and beyond 1 km) under various environmental conditions. This provides essential guidance in the design of the sending and receiving arrays of high-speed underwater communications systems, which rely on multiplexing acoustic OAMs.