Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Communication Versus Computation: Duality for Multiple-Access Channels and Source Coding
 
research article

Communication Versus Computation: Duality for Multiple-Access Channels and Source Coding

Zhu, Jingge
•
Lim, Sung Hoon
•
Gastpar, Michael C.  
2019
IEEE Transactions on Information Theory

Computation codes in network information theory are designed for scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. Körner and Marton showed for distributed source coding (DSC) that such function decoding can be achieved more efficiently than decoding the full information sources. Compute–forward has shown that function decoding, in combination with network coding ideas, is a useful building block for end-to-end communication over a network. In both cases, good computation codes are the key component in the coding schemes. Could these same codes simultaneously also enable full message decoding over a sufficiently strong multiple-access channel (MAC)? This work establishes a partial negative answer and converse result. Specifically, for any code that is known to be a good computation code for some MAC, we characterize a class of MACs for which that code cannot enable full message decoding (and vice versa). Finally, an analogous duality result is established for a related DSC problem.

  • Details
  • Metrics
Type
research article
DOI
10.1109/TIT.2018.2849971
Author(s)
Zhu, Jingge
Lim, Sung Hoon
Gastpar, Michael C.  
Date Issued

2019

Published in
IEEE Transactions on Information Theory
Volume

65

Issue

1

Start page

292

End page

301

Subjects

Function computation

•

code duality

•

multiple access channel

•

compute–forward

•

multi-terminal source coding

•

structured code

•

Decoding

•

Source coding

•

Network coding

•

Receivers

•

Probability distribution

•

Communication networks

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LINX  
Available on Infoscience
January 11, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/153429
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés