Distributed Compression in Acoustic Sensor Networks using Oversampled A/D Conversion
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