| Paper: | SS-5.7 | ||
| Session: | Signal Processing for Wireless Sensor Networks II | ||
| Time: | Wednesday, May 19, 14:42 - 14:59 | ||
| Presentation: | Special Session Lecture | ||
| Topic: | Special Sessions: Signal Processing for Wireless Sensor Networks | ||
| Title: | ASYMPTOTICALLY OPTIMAL DECENTRALIZED TYPE-BASED DETECTION IN WIRELESS SENSOR NETWORKS | ||
| Authors: | Ke Liu; University of Wisconsin-Madison | ||
| Akbar M. Sayeed; University of Wisconsin-Madison | |||
| Abstract: | We propose a novel decentralized detection schemebased on the method of types and type detectors. Contrary toconventional methods, the proposed decentralized type detection(DTD) scheme asymptotically achieves the performance of centralizeddetection, provided there exists an arbitrarily small (butnon-zero) communication capacity between the sensing nodes andthe decision center. The sensing nodes extract and transmit thetype information of the observed data sequence, which is thenrecovered and used by a type detector at the decision center.The key to DTD is that the required network information flow(type information) is of asymptotically vanishing entropy ratebut still sufficient for the hypothesis testing problem. The simplestructure of type sensors greatly reduces system cost in termsof computational and communication capabilities for sensornodes. In particular, the sensor nodes need not know the signalstatistics under different hypothesis. Theoretical analysis andnumerical simulations demonstrate the excellent performance ofthe proposed DTD scheme. | ||
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