Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.
We address the problem of distributed compression in acoustic sensor networks. A typical scenario consists of a set of microphones that record a sound source located at some unknown position. The goal then is to convey the corresponding audio signals to a central base station for processing. We thus aim at designing efficient distributed communication schemes that minimize the overall bit-rate needed in order to achieve a given reconstruction accuracy. In this paper, we show how the a priori knowledge of the system's geometry can be beneficially used in order to lower the transmission rates. We propose a distributed coding scheme for simple synthetic sources. These results are then applied to more general signals by means of oversampled analog-to-digital conversion. Simulation results confirm the effectiveness of our approach.
David Atienza Alonso, Vincent Stadelmann, Tomas Teijeiro Campo, Jérôme Paul Rémy Thevenot, Christodoulos Kechris