Online distributed waveform-synchronization for acoustic sensor networks with dynamic topology

Abstract Acoustic sensing by multiple devices connected in a wireless acoustic sensor network (WASN) creates new opportunities for multichannel signal processing. However, the autonomy of agents in such a network still necessitates the alignment of sensor signals to a common sampling rate. It has be...

Full description

Bibliographic Details
Main Authors: Aleksej Chinaev, Niklas Knaepper, Gerald Enzner
Format: Article
Language:English
Published: SpringerOpen 2023-12-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Subjects:
Online Access:https://doi.org/10.1186/s13636-023-00311-9
Description
Summary:Abstract Acoustic sensing by multiple devices connected in a wireless acoustic sensor network (WASN) creates new opportunities for multichannel signal processing. However, the autonomy of agents in such a network still necessitates the alignment of sensor signals to a common sampling rate. It has been demonstrated that waveform-based estimation of sampling rate offset (SRO) between any node pair can be retrieved from asynchronous signals already exchanged in the network, but connected online operation for network-wide distributed sampling-time synchronization still presents an open research task. This is especially true if the WASN experiences topology changes due to failure or appearance of nodes or connections. In this work, we rely on an online waveform-based closed-loop SRO estimation and compensation unit for nodes pairs. For WASNs hierarchically organized as a directed minimum spanning tree (MST), it is then shown how local synchronization propagates network-wide from the root node to the leaves. Moreover, we propose a network protocol for sustaining an existing network-wide synchronization in case of local topology changes. In doing so, the dynamic WASN maintains the MST topology after reorganization to support continued operation with minimum node distances. Experimental evaluation in a simulated apartment with several rooms proves the ability of our methods to reach and sustain accurate SRO estimation and compensation in dynamic WASNs.
ISSN:1687-4722