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Optimized compressed sensing matrix design for noisy communication channels
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We investigate a power-constrained sensing matrix design problem for a compressed sensing framework. We adopt a mean square error (MSE) performance criterion for sparse source reconstruction in a system where the source-to-sensor channel and the sensor-to-decoder communication channel are noisy. Our proposed sensing matrix design procedure relies upon minimizing a lower-bound on the MSE. Under certain conditions, we derive closed-form solutions to the optimization problem. Through numerical experiments, by applying practical sparse reconstruction algorithms, we show the strength of the proposed scheme by comparing it with other relevant methods. We discuss the computational complexity of our design method, and develop an equivalent stochastic optimization method to the problem of interest that can be solved approximately with a significantly less computational burden. We illustrate that the low-complexity method still outperforms the popular competing methods.

Place, publisher, year, edition, pages
2015.
Series
IEEE International Conference on Communications, ISSN 1550-3607
National Category
Signal Processing
Research subject
Electrical Engineering with specialization in Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-253314ISI: 000371708104126ISBN: 9781467364324 (print)OAI: oai:DiVA.org:uu-253314DiVA: diva2:814128
Conference
IEEE International Conference on Communications (ICC), London, UK
Available from: 2015-05-26 Created: 2015-05-26 Last updated: 2016-07-13Bibliographically approved

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Shirazinia, AmirpashaDey, Subhrakanti

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  • apa
  • ieee
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
  • rtf