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

Title
Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions
Author(s)
Lim, S.H.; Feng, C.; Pastore, A.; Nazer, B.; Gastpar, M.
Publication Year
2019-07-12
Abstract
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. © 2019 IEEE.
ISSN
2157-8095
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/22551
Bibliographic Citation
2019 IEEE International Symposium on Information Theory, pp.1827 - 1831, 2019
Publisher
Institute of Electrical and Electronics Engineers Inc.
Type
Conference
Language
English
Publisher
Institute of Electrical and Electronics Engineers Inc.
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