Abstract

Active Wireless Sensing (AWS) was recently proposed as a promising framework for information extraction in wireless sensor networks. In AWS, a wireless information retriever (WIR), equipped with an antenna array, interrogates a select ensemble of sensors with wideband space-time waveforms for rapid and energy-efficient retrieval of sensor information. The WIR extracts sensor information by exploiting the differences in the space-time signatures associated with distinct sensors. In this paper, we investigate the challenging problem of AWS in multipath environments. Our results show that the use of wideband waveforms in AWS allows for exploitation of multipath scattering in two important aspects: higher energy capture and improved sensor resolution, and consequently improved energy efficiency and larger information retrieval rates. These advantages are first quantified through improved reliability and increased capacity of information retrieval for a given sensor transmission energy. A time-reversal technique is also proposed for simultaneously addressing individual sensors. Our results indicate that the richer the multipath, the sharper the ability to address individual sensors while limiting the interference to other sensors. The theoretical development is supported with realistic numerical results.

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