Sparse recovery using sparse sensing matrix based finite field optimization in network coding

Ganzorig Gankhuyag, Eungi Hong, Yoonsik Choe

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Network coding (NC) is considered a new paradigm for distributed networks. However, NC has an all-or-nothing property. In this paper, we propose a sparse recovery approach using sparse sensing matrix to solve the NC all-or-nothing problem over a finite field. The effectiveness of the proposed approach is evaluated based on a sensor network.

Original languageEnglish
Pages (from-to)375-378
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE100D
Issue number2
DOIs
Publication statusPublished - 2017 Feb 1

Fingerprint

Network coding
Recovery
Sensor networks

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Cite this

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Sparse recovery using sparse sensing matrix based finite field optimization in network coding. / Gankhuyag, Ganzorig; Hong, Eungi; Choe, Yoonsik.

In: IEICE Transactions on Information and Systems, Vol. E100D, No. 2, 01.02.2017, p. 375-378.

Research output: Contribution to journalArticle

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