NDLI: Study on performance behavior of compressive sensing measurements for multiple sensor system

Content Provider	IEEE Xplore Digital Library
Author	Sangjun Park Hwanchol Jang Heung-no Lee
Copyright Year	2011
Description	Author affiliation: Information and Communications, Gwangju Institute of Science and Technology, Republic of Korea (Sangjun Park; Hwanchol Jang; Heung-no Lee)
Abstract	In this paper, we will analyze the performance limit for a multiple sensor system (MSS) based on compressive sensing. In our MSS, all of the sensors measure signals from a common source. There exists the redundancy in the measured signal because the measured signal comes from the common source. To reduce communication costs, this redundancy must be removed. For this purpose, we use compressive sensing at each sensor to obtain compressed measurements. After all of the sensors obtain compressed measurements, they transmit them to a central unit. A decoder at the central unit receives all of the transmitted signals and attempts to jointly estimate the correct support set, which is the set of indices corresponding to the locations of the non-zero coefficients of the measured signals. In order to analyze our MSS, we present a jointly typical decoder inspired by recent work [4]. We first obtain the upper bound probability that the jointly typical decoder fails to estimate the correct support set. Next, we prove that as the number of sensors increases, the compressed measurements per sensor (per-sensor measurements) can be reduced to sparsity, which is the number of non-zero coefficients in the measured signal. We present the sufficient number of sensors required with the increase in the noise variance.
Starting Page	1980
Ending Page	1983
File Size	444881
Page Count	4
File Format	PDF
ISBN	9781467303217
ISSN	10586393
e-ISBN	9781467303231
DOI	10.1109/ACSSC.2011.6190371
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decoding Noise Compressed sensing Redundancy Sensors Vectors Upper bound Per-Sensor Measurements Multiple Sensor System Joint Typicality Compressive Sensing Sparse Signal
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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