Over the past year, I’ve fallen in love with Julia. Now most of my acoustics, signal processing, data analysis, and machine learning research is done in Julia. So it’s natural for me to ask how I can use Julia with UnetStack, as a lot of that research eventually finds its way into underwater networks via UnetStack. In this 2-part article, we’ll explore 2 different ways to get Julia and UnetStack to work seamlessly together.
Underwater acoustic (UWA) networks are already playing a key role in many areas including marine, offshore and subsea industries. There have been tremendous and impressive technological advances in underwater acoustic communications and networking field. The one that caught my attention and brought about a clear difference in the novel approaches that are needed to deal with challenges in UWA networks was the “exploitation” of large propagation delays that exist in UWA networks.
UnetStack 3.0, released at the end of September last year, was a major milestone in the evolution of UnetStack. We are now excited to release the next installment of features and performance enhancements in the form of UnetStack 3.1. Apart from performance enhancements and bug fixes, UnetStack 3.1 brings significant feature upgrades to the link, ranging and routing services, new concepts such as wormholes and distributed spatial diversity, a new fragmentation-reassembly framework, and improved user interface in the form of dashboards.
Spatial diversity techniques that are used in terrestrial networks usually utilize multiple antennas on the same device to improve link quality and reliability. Similarly, having multiple hydrophones/transducers on the same underwater node might help with the same but comes with the cost of a significant increase in the size due to the spatial separation that might be needed between transducers. Can we exploit a similar technique to make underwater wireless networks faster and more reliable and make that long-range communication link “just work”? With the capability to exploit distributed spatial diversity, yes you can!
MATLAB is widely known as a high-quality environment for any work that invlolves arrays, matrices or linear algebra and hence is extremely useful for scientific computing. If you are a MATLAB user and wondering if you can interact with the modems running UnetStack, the answer is yes. In this blog, you will learn how to: