Utilization of partial common information in distributed compressive sensing

Jeong Hun Park, Seung Gye Hwang, Dong Ku Kim, Jang Hoon Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In a densely distributed sensor network, it is known that it is advantageous to exploit both intra- and inter- signal correlation structures during recovery procedure. Based on this observation, the bound of the required number of measurement in distributed compressive sensing (DCS) is shown to be reduced by exploiting this structure[2]. In this paper, we generalize the model for distributed compressive sensing and show that elaborated signal structure can reduce the required number of measurements further. To this end, we introduce a new concept of partial common information which is shared by some parts of signals, but not by every signal. Numerical results show that with the proposed model, more robust signal recovery can be achieved.

Original languageEnglish
Title of host publicationIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings
DOIs
Publication statusPublished - 2012
EventIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Yokohama, Japan
Duration: 2012 May 62012 Jun 9

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Other

OtherIEEE 75th Vehicular Technology Conference, VTC Spring 2012
CountryJapan
CityYokohama
Period12/5/612/6/9

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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    Park, J. H., Hwang, S. G., Kim, D. K., & Yang, J. H. (2012). Utilization of partial common information in distributed compressive sensing. In IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings [6240176] (IEEE Vehicular Technology Conference). https://doi.org/10.1109/VETECS.2012.6240176