Rate-distortion lower bound for compressed sensing via conditional remote source coding

Markus Leinonen; Marian Codreanu; Markku Juntti; Gerhard Kramer

doi:10.1109/ITW.2016.7606839

Rate-distortion lower bound for compressed sensing via conditional remote source coding

Markus Leinonen, Marian Codreanu, Markku Juntti, Gerhard Kramer

Chair of Communications Engineering

University of Oulu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Lossy compressed sensing (CS) of a sparse source is studied. A lower bound to the best achievable compression performance in a finite rate CS setup is established by providing support side information to the encoder and decoder. The rate-distortion problem is formulated via remote source coding and conditional rate-distortion theory. The best encoder separates into an estimation step and a rate-dependent transmission step. Numerical results illustrate the rate-distortion behavior of the scheme.

Original language	English
Title of host publication	2016 IEEE Information Theory Workshop, ITW 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	275-279
Number of pages	5
ISBN (Electronic)	9781509010905
DOIs	https://doi.org/10.1109/ITW.2016.7606839
State	Published - 21 Oct 2016
Event	2016 IEEE Information Theory Workshop, ITW 2016 - Cambridge, United Kingdom Duration: 11 Sep 2016 → 14 Sep 2016

Publication series

Name	2016 IEEE Information Theory Workshop, ITW 2016

Conference

Conference	2016 IEEE Information Theory Workshop, ITW 2016
Country/Territory	United Kingdom
City	Cambridge
Period	11/09/16 → 14/09/16

Access to Document

10.1109/ITW.2016.7606839

Cite this

Leinonen, M., Codreanu, M., Juntti, M., & Kramer, G. (2016). Rate-distortion lower bound for compressed sensing via conditional remote source coding. In 2016 IEEE Information Theory Workshop, ITW 2016 (pp. 275-279). Article 7606839 (2016 IEEE Information Theory Workshop, ITW 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITW.2016.7606839

@inproceedings{67931ce2f04d48128f91f462d462292e,

title = "Rate-distortion lower bound for compressed sensing via conditional remote source coding",

abstract = "Lossy compressed sensing (CS) of a sparse source is studied. A lower bound to the best achievable compression performance in a finite rate CS setup is established by providing support side information to the encoder and decoder. The rate-distortion problem is formulated via remote source coding and conditional rate-distortion theory. The best encoder separates into an estimation step and a rate-dependent transmission step. Numerical results illustrate the rate-distortion behavior of the scheme.",

author = "Markus Leinonen and Marian Codreanu and Markku Juntti and Gerhard Kramer",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Information Theory Workshop, ITW 2016 ; Conference date: 11-09-2016 Through 14-09-2016",

year = "2016",

month = oct,

day = "21",

doi = "10.1109/ITW.2016.7606839",

language = "English",

series = "2016 IEEE Information Theory Workshop, ITW 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "275--279",

booktitle = "2016 IEEE Information Theory Workshop, ITW 2016",

}

Leinonen, M, Codreanu, M, Juntti, M & Kramer, G 2016, Rate-distortion lower bound for compressed sensing via conditional remote source coding. in 2016 IEEE Information Theory Workshop, ITW 2016., 7606839, 2016 IEEE Information Theory Workshop, ITW 2016, Institute of Electrical and Electronics Engineers Inc., pp. 275-279, 2016 IEEE Information Theory Workshop, ITW 2016, Cambridge, United Kingdom, 11/09/16. https://doi.org/10.1109/ITW.2016.7606839

Rate-distortion lower bound for compressed sensing via conditional remote source coding. / Leinonen, Markus; Codreanu, Marian; Juntti, Markku et al.
2016 IEEE Information Theory Workshop, ITW 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 275-279 7606839 (2016 IEEE Information Theory Workshop, ITW 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Rate-distortion lower bound for compressed sensing via conditional remote source coding

AU - Leinonen, Markus

AU - Codreanu, Marian

AU - Juntti, Markku

AU - Kramer, Gerhard

PY - 2016/10/21

Y1 - 2016/10/21

N2 - Lossy compressed sensing (CS) of a sparse source is studied. A lower bound to the best achievable compression performance in a finite rate CS setup is established by providing support side information to the encoder and decoder. The rate-distortion problem is formulated via remote source coding and conditional rate-distortion theory. The best encoder separates into an estimation step and a rate-dependent transmission step. Numerical results illustrate the rate-distortion behavior of the scheme.

AB - Lossy compressed sensing (CS) of a sparse source is studied. A lower bound to the best achievable compression performance in a finite rate CS setup is established by providing support side information to the encoder and decoder. The rate-distortion problem is formulated via remote source coding and conditional rate-distortion theory. The best encoder separates into an estimation step and a rate-dependent transmission step. Numerical results illustrate the rate-distortion behavior of the scheme.

UR - http://www.scopus.com/inward/record.url?scp=84998546746&partnerID=8YFLogxK

U2 - 10.1109/ITW.2016.7606839

DO - 10.1109/ITW.2016.7606839

M3 - Conference contribution

AN - SCOPUS:84998546746

T3 - 2016 IEEE Information Theory Workshop, ITW 2016

SP - 275

EP - 279

BT - 2016 IEEE Information Theory Workshop, ITW 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE Information Theory Workshop, ITW 2016

Y2 - 11 September 2016 through 14 September 2016

ER -

Rate-distortion lower bound for compressed sensing via conditional remote source coding

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this