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Software Defined Acoustic Modems

Friday May 11, 2007
Hamerschlag Hall 1112
12:00 pm

Ryan Kastner
UC Santa Barbara

The aquatic research community is rapidly equipping ecological sites with a broad range of sensors and instruments. However, the development of underwater sensing networks is significantly lagging terrestrial counterparts. It is widely recognized that an equivalent to low cost, low power, wireless radios is needed to advance the state-of-the-art in underwater sensor networks. Unfortunately, there are few open-architecture, energy efficient, low cost acoustic modems. Existing modems either use proprietary hardware or digital signal processors. While digital signal processors are sufficient for simple modulation, they are power hungry and cannot handle the computational demands of more complex physical layer protocols. This talk describes an alternative hardware platform for wireless underwater communication. Reconfigurable computing devices are used to create a software defined acoustic modem (SDAM) – the underwater counterpart to software defined radios being proposed for future generations of terrestrial communications. The SDAM can be remotely programmed, which enables adaptive sensing capabilities and changes to the network without physically retrieving the device. Since the communication protocol is programmed into the modem, the same SDAM board can be used for a variety of different underwater environments.

The talk starts by describing recent work on the UCSB AquaNode - an integrated sensor, software defined acoustic modem and hardware platform that can operate in a low-energy acoustic network to provide real-time sensor measurements. We are currently developing two modems for the AquaNode – a “Mooring modem” (for use in sensor networks on ocean and lake moorings) and a “Moorea modem” (for sensor networks in the coral reef lagoon surrounding the island of Moorea). In order to facilitate the understanding of the major design problems, we focus on the implementation of the “Moorea modem”, in particular, the development of an acoustic receiver for wireless communication in littoral zones. This shallow water acoustic channel is highly bandlimited and plagued by noise, multipath, Doppler spreads and variable propagation delays. Therefore, the acoustic receiver uses a direct sequence spread spectrum modulation that requires a computationally intensive algorithm for demodulation. An implementation on a reconfigurable device is described, which enables an energy efficient, real-time receiver. The key is a cross-cutting approach with novel optimizations at every level, from theory and algorithms to arithmetic, data distribution and computational partitioning.

Ryan Kastner is an associate professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara. He received a PhD in Computer Science (2002) at UCLA, a masters degree in engineering (2000) and bachelor degrees (BS) in both electrical engineering and computer engineering (1999), all from Northwestern University. He is the director of the Extensible, Programmable, Reconfigurable Embedded Systems (ExPRESS) lab at UCSB. His current research interests fall within the realm of embedded system design, in particular, the use of reconfigurable computing devices for digital signal processing.

Professor Kastner has published over 80 technical articles, and is the author of the book, “Synthesis Techniques and Optimizations for Reconfigurable Systems”. He is a member of numerous conference technical committees including the International Conference on Computer Aided Design (ICCAD), the Design Automation Conference (DAC), Design, Automation and Test in Europe (DATE) , GLOBECOM, the International Conference on Computer Design (ICCD), the Great Lakes Symposium on VLSI (GLSVLSI), the International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA) and the International Symposium on Circuits and Systems (ISCAS). He serves on the editorial board for the Journal of Embedded Computing.


Department of Electrical and Computer EngineeringCarnegie Mellon UniversitySchool of Computer Science