Active Wireless Sensing: A Versatile Framework for Information Retrieval in Sensor Networks

Many existing information processing schemes in sensor networks are based on multihop in-network algorithms that require information routing and coordination between nodes and incur excess overhead in latency and energy consumption. In this paper, we develop an alternative and complementary single-hop approach - 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. The basic architecture in AWS consists of:(i) a WIR, equipped with an antenna array, interrogates the wireless sensors with wideband space-time waveforms, (ii) the sensors modulate the acquired waveforms with their (possibly encoded) measured data and generate an ensemble response to the WIR´s interrogation signal, and (iii) the WIR extracts the sensor data by exploiting the space-time characteristics of the resulting multipath sensing channel. To facilitate analysis, we propose a canonical family of sensing configurations that represent a simple abstraction of spatial correlation in the signal field or the nature of local cooperation in the network. The concept of source-channel matching is introduced in which the spatio-temporal resolution is adapted to the spatial scale of node correlation in the sensing configurations. Signaling strategies and associated receiver structures at the WIR are developed for different source-channel matching configurations. The performance of AWS is analyzed in different configurations both in terms of reliability and capacity of information retrieval.