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  4. Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions
 
conference paper

Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions

Lim, Sung Hoon
•
Feng, Chen
•
Pastore, Adriano
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July 7, 2019
2019 IEEE International Symposium on Information Theory (ISIT)
2019 IEEE International Symposium on Information Theory (ISIT)

Consider the important special case of the K-user distributed source coding problem where the decoder only wishes to recover one or more linear combinations of the sources. The work of Körner and Marton demonstrated that, in some cases, the optimal rate region is attained by random linear codes, and strictly improves upon the best-known achievable rate region established via random i.i.d. codes. Recent efforts have sought to develop a framework for characterizing the achievable rate region for nested linear codes via joint typicality encoding and decoding. Here, we make further progress along this direction by proposing an achievable rate region for simultaneous joint typicality decoding of nested linear codes. Our approach generalizes the results of Körner and Marton to computing an arbitrary number of linear combinations and to the lossy computation setting.

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Type
conference paper
DOI
10.1109/ISIT.2019.8849363
Web of Science ID

WOS:000489100301184

Author(s)
Lim, Sung Hoon
Feng, Chen
Pastore, Adriano
Nazer, Bobak
Gastpar, Michael  
Date Issued

2019-07-07

Published in
2019 IEEE International Symposium on Information Theory (ISIT)
Start page

1827

End page

1831

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LINX  
Event nameEvent placeEvent date
2019 IEEE International Symposium on Information Theory (ISIT)

Paris, France

July 7-12, 2019

Available on Infoscience
October 11, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/161958
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