# Technical Program

## Paper Detail

 Paper: SS-7.7 Session: Distributed Digital Signal Processing for Sensor Networking Time: Thursday, May 20, 11:00 - 11:15 Presentation: Special Session Lecture Topic: Special Sessions: Distributed Digital Signal Processing for Sensor Networking Title: ON DISTRIBUTED SAMPLING OF BANDLIMITED AND NON-BANDLIMITED SENSOR FIELDS Authors: Animesh Kumar; University of California, Berkeley Prakash Ishwar; University of California, Berkeley Kannan Ramchandran; University of California, Berkeley Abstract: Distributed sampling and reconstruction of a physical field using an array of sensors is a problem of increasing interest in environmental monitoring applications of sensor networks. This work addresses the related sampling framework in the context of both bandlimited and non-bandlimited sensor fields. We show, using a dither-based scheme, that it is possible to reconstructnon-bandlimited fields with a reconstruction accuracy that depends on the available bitrate $R$ and the spectral decay characteristics of the sensor field -- we study exponentially decaying spectra as an illustration. For bandlimited fields $f(t)$, the maximum pointwise error $D_f$ decays as $D_f \sim 2^{-a_1 R}$, i.e. exponentially with rate $R$. For the non-bandlimited case, we show that for fields $u(t)$ with exponentially decaying spectral tails, i.e., $|U(\omega)| \sim e^{-a|\omega|}$, the maximum pointwise error $D_{u}$ decays as $D_{u} \sim e^{-a_2\sqrt{R}}(1+o(R))$ with spatial bit rate $R$ bits/meter. We also show that it is possible to trade off the number of sensors with their precision, while maintaining a similar reconstruction accuracy -- a phenomenon that may be dubbed as a {\it bit-conservation''} principle underlying the sampling framework. Back

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