Software-defined underwater acoustic networking platform and its applications

As underwater communications adopt acoustics as the primary modality, we are confronting several unique challenges such as highly limited bandwidth, severe fading, and long propagation delay. To cope with these, many MAC protocols and PHY layer techniques have been proposed. In this paper, we present a research platform that allows developers to easily implement and compare their protocols in an underwater network and configure them at runtime. We have built our platform using widely supported software that has been successfully used in terrestrial radio and network development. The flexibility of development tools such as software defined radio, TinyOS, and Linux have provided the ability for rapid growth in the community. Our platform adapts some of these tools to work well with the underwater environment while maintaining flexibility, ultimately providing an end-to-end networking approach for underwater acoustic development. To show its applicability, we further implement and evaluate channel allocation and time synchronization protocols on our platform. The underwater medium presents many challenges for digital communication. There is limited available bandwidth and high bit error rates caused by multipath, fading, and long propagation delay. The speed of sound is five orders of magnitude less than that of terrestrial radio, which can make it hard for underwater networks to synchronize, exchange data, update routes, and communicate efficiently. Due to the severity of multipath underwater, a receiving node might be at a point where there is little energy in the received signal making it hard to receive without errors [1]. These spots of destructive multipath interference vary with time due to the movement of water, and make it quite hard to even have a static network topology. Along with multipath, other unfavorable characteristics such as ambient noise, bubbles, surface scattering, and slow propagation speed make developing underwater networks a difficult task [1]. Furthermore, the ocean varies significantly both temporally and spatially, which makes it challenging to create a model of a ''typical'' underwater acoustic channel [1]. Since there is no ''typical'' model, there is no single network architecture that works best in all situations. Therefore, depending on the current characteristics of the channel, there is a variable amount of bandwidth, various noise sources in different frequency bands, varying inter-symbol interference (ISI) depending on the water depth, and many other characteristics under consideration. Even if the channel noise is known, attenuation still depends on both distance and frequency, along with space and time varying multipath …