대수학 네트워크 정보이론: 동시적 joint typicality 복호화 기법

Title
대수학 네트워크 정보이론: 동시적 joint typicality 복호화 기법
Alternative Title
Towards an Algebraic Network Information Theory: Simultaneous Joint Typicality Decoding
Author(s)
임성훈; Chen Feng; Adriano Pastore; Bobak Nazer; Michael Gastpar
Alternative Author(s)
임성훈
Publication Year
2017-06-28
Abstract
Recent work has employed joint typicality encoding and decoding of nested linear code ensembles to generalize the compute– forward strategy to discrete memoryless multiple-access channels (MACs). An appealing feature of these nested linear code ensembles is that the coding strategies and error probability bounds are conceptually similar to classical techniques for random i.i.d. code ensembles. In this paper, we consider the problem of recovering K linearly independent combinations over a K-user MAC, i.e., recovering the messages in their entirety via nested linear codes. While the MAC rate region is well understood for random i.i.d. code ensembles, new techniques are needed to handle the statistical dependencies between competingcodeword K-tuples that occur in nested linear code ensembles.near code ensembles is that the coding strategies and error probability bounds are conceptually similar to classical techniques for random i.i.d. code ensembles. In this paper, we consider the problem of recovering K linearly independent combinations over a K-user MAC, i.e., recovering the messages in their entirety via nested linear codes. While the MAC rate region is well understood for random i.i.d. code ensembles, new techniques are needed to handle the statistical dependencies between competingcodeword K-tuples that occur in nested linear code ensembles.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23922
Bibliographic Citation
International Symposium on Information Theory, pp.1818 - 1822, 2017
Publisher
IEEE
Type
Conference
Language
English
Publisher
IEEE
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