Network-Aware Optimal Microphone Channel Selection in Wireless Acoustic Sensor Networks

• Published in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 820 - 824
• Main Authors: Gunther, Michael, Afifi, Haitham, Brendel, Andreas, Karl, Holger, Kellermann, Walter
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.06.2021
• Subjects: Acoustic sensors; Approximation algorithms; channel selection; Correlation; Cost function; graph theory; microphone utility; Signal processing algorithms; wireless acoustic sensor network; Wireless networks; Wireless sensor networks
• DOI: 10.1109/ICASSP39728.2021.9414528

To address the vital problem of selecting the most useful microphones in wireless acoustic sensor networks, this paper proposes a novel, general-purpose approach that accounts for both acoustic and network aspects and remains application-agnostic for broad applicability. The inter-channel correlation of single-channel signal features, together with tools from spectral graph theory, is used to assess the usefulness from an acoustic perspective. By only transmitting the features that characterize signal frames as opposed to the full signal waveform, the unique constraints of wireless sensor networks are accommodated. The source-to-sink transmission delay, resulting from embedding a distributed signal processing application into a wireless network, captures the usefulness from a network perspective. The experiments demonstrate the efficacy of the proposed method for an exemplary multichannel signal processing application.