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

Abstract

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.

PyAWNeS-Codec: Speech and audio codec for ad-hoc acoustic wireless sensor networks

“…On the other hand, distributed source coding techniques for WASNs have been widely studied, e.g. [5]- [11], but as far as we know, none of such contributions have resulted in a publicly available implementation of a codec, which would reach a competitive performance also in a single-channel mode. In particular, most such works have studied rate-distortion theory, but have not actually implemented a quantizer and codec.…”

RIDA: A Robust Information-Driven Data Compression Architecture for Irregular Wireless Sensor Networks

“…Few other works in distributed audio and video compression in wireless sensor networks can be found at [15][16] [5]. Other approaches [17][18] try to solve multiple goals such as routing, aggregation, indexing and storage, and energy balancing with compression.…”