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

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. The inter-channel correlation of single-channel signal features, together with tools from spectral graph theory, is used to assess the usefulness of microphone signals 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, acoustic 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.