Adaptive Sampling and Diversity Reception in Multi-hop Wireless Audio Sensor Networks

Wireless Audio Sensor Networks (WASNs) can provide event detection, object tracking and audio stream monitoring through cooperative audio sensor nodes. Extensive researches have focused on sound detection and source localization, but little work is on the monitoring and recovery of audio stream. To clearly reconstruct the real-time audio stream from WASNs, both the quantity and quality of samples provided by sensor nodes should be carefully considered. In this work, we propose a novel approach termed "adaptive sampling and diversity reception", which can significantly reduce the energy consumption of network while maintaining high accuracy of audio stream. On one hand, by selectively picking sampling nodes and adaptively adjusting their sampling rates, sufficient samples arrive at the fusion node for high recovering fidelity. On the other hand, through Maximal-Ratio-Combining(MRC)-like signal fusion scheme at the fusion node, the signal-to-noise ratio (SNR) of combined audio is further improved. Meanwhile, we propose a heuristic algorithm of sampling rate assignment which can select a set of optimal sampling nodes and hence minimize the energy consumption on data transmission. Analytically and experimentally, we show that the proposed scheme can improve the signal recovering fidelity tremendously with low energy cost.