Space-time Reversal Techniques for Information Retrieval in Wireless Sensor Networks

In this paper, we explore the benefits of space-time reversal (STR) techniques in the context of information retrieval in wireless sensor networks under the recently proposed Active Wireless Sensing (AWS) framework. In AWS, individual sensors are differentiated via their distinct space-time signatures and STR schemes exploit these sensor signatures. In the downlink, STR techniques are proposed to address individual sensors thus enabling sensor programming for different information retrieval or sensing modes. In the uplink, we propose an STR scheme for localizing distinct sensor responses to distinct signal space dimensions at the WIR thereby reducing interference between sensor transmissions. Furthermore, it does not require explicit estimation of sensor signatures at the WIR. The benefits of STR techniques in both scenarios are quantified analytically and illustrated with physically meaningful simulation results.