Active wireless sensing for rapid information retrieval in sensor networks

Most existing information extraction schemes in sensor networks rely on in-network processing that requires information routing and coordination between sensor nodes and incurs a corresponding overhead in delay and energy consumption. In this paper, we propose a viable alternative-active wireless sensing (AWS)-in which a wireless information retriever (WIR) queries a select ensemble of nodes to obtain desired information in a rapid and energy-efficient manner. AWS has two primary attributes: i) the sensor nodes are "dumb" in that they have limited computational ability, and ii) the WIR, is computationally powerful, is equipped with an antenna array, and directly interrogates the sensor ensemble with wideband space-time waveforms. AWS is inspired by an intimate connection with communication over multipath channels: the sensor nodes act as active scatterers and produce a multipath response to the WIR's interrogation signals. We develop the basic communication architecture in AWS and explore various signaling and reception strategies at the WIR, and encoding strategies at the sensors. The basic communication architecture is quite flexible and can cater to a variety of information retrieval tasks. In particular, we illustrate the framework in two extreme information retrieval tasks: high-rate information retrieval corresponding to distributed independent sensor measurements, and low-rate retrieval corresponding to localized correlated measurements. A low-complexity interference suppression technique is proposed for significantly increasing the capacity and reliability of high-rate information retrieval. Performance analysis reveals a fundamental rate versus reliability tradeoff in AWS and is illustrated with accompanying simulation results