Big Data Technologies and Applications. 7th International Conference, BDTA 2016, Seoul, South Korea, November 17–18, 2016, Proceedings

Research Article

Distributed Compressive Sensing for Correlated Information Sources

Download
172 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-58967-1_15,
        author={Jeonghun Park and Seunggye Hwang and Janghoon Yang and Kitae Bae and Hoon Ko and Dong Kim},
        title={Distributed Compressive Sensing for Correlated Information Sources},
        proceedings={Big Data Technologies and Applications. 7th International Conference, BDTA  2016, Seoul, South Korea, November 17--18, 2016, Proceedings},
        proceedings_a={BDTA},
        year={2017},
        month={6},
        keywords={Compressive sensing Distributed source coding Sparsity Random projection Sensor networks},
        doi={10.1007/978-3-319-58967-1_15}
    }
    
  • Jeonghun Park
    Seunggye Hwang
    Janghoon Yang
    Kitae Bae
    Hoon Ko
    Dong Kim
    Year: 2017
    Distributed Compressive Sensing for Correlated Information Sources
    BDTA
    Springer
    DOI: 10.1007/978-3-319-58967-1_15
Jeonghun Park1,*, Seunggye Hwang2,*, Janghoon Yang3,*, Kitae Bae3,*, Hoon Ko4,*, Dong Kim5,*
  • 1: University of Texas at Austin
  • 2: LG Electronics
  • 3: Seoul Media Institute of Technology
  • 4: Sungkyunkwan University
  • 5: Yonsei University
*Contact email: the20thboys@gmail.com, pisces_sg@yonsei.ac.kr, jhyag@smit.ac.kr, ktbae@smit.ac.kr, skoh21@skku.edu, dkkim@yonsei.ac.kr

Abstract

The abstract should summarize the contents of the paper and should Distributed Compressive Sensing (DCS) improves the signal recovery performance of multi signal ensembles by exploiting both intra- and inter-signal correlation and sparsity structure. In this paper, we propose a novel algorithm, which improves detection performance even without a priori-knowledge on the correlation structure for arbitrarily correlated sparse signal. Numerical results verify that the propose algorithm reduces the required number of measurements for correlated sparse signal detection compared to the existing DCS algorithm.