Binary Systematic Network Coding for Progressive Packet Decoding

Andrew L. Jones; Ioannis Chatzigeorgiou; Andrea Tassi

Binary Systematic Network Coding for Progressive Packet Decoding

Andrew L. Jones, Ioannis Chatzigeorgiou, Andrea Tassi

Department of Electrical & Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

22 Citations (Scopus)

17 Downloads (Pure)

Abstract

We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional network coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve the theoretical optimal performance. Furthermore, we demonstrate that systematic network codes equipped with the proposed algorithm are good candidates for progressive packet recovery owing to their overall decoding delay characteristics.

Original language	English
Title of host publication	IEEE ICC 2015 - Communication Theory Symposium
Publication status	Published - 14 Jan 2015

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Proc. of IEEE ICC 2015 - Communication Theory Symposium

Keywords

cs.IT
cs.MM
cs.PF
math.IT

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title = "Binary Systematic Network Coding for Progressive Packet Decoding",

abstract = "We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional network coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve the theoretical optimal performance. Furthermore, we demonstrate that systematic network codes equipped with the proposed algorithm are good candidates for progressive packet recovery owing to their overall decoding delay characteristics.",

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AU - Chatzigeorgiou, Ioannis

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N1 - Proc. of IEEE ICC 2015 - Communication Theory Symposium

PY - 2015/1/14

Y1 - 2015/1/14

N2 - We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional network coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve the theoretical optimal performance. Furthermore, we demonstrate that systematic network codes equipped with the proposed algorithm are good candidates for progressive packet recovery owing to their overall decoding delay characteristics.

AB - We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional network coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve the theoretical optimal performance. Furthermore, we demonstrate that systematic network codes equipped with the proposed algorithm are good candidates for progressive packet recovery owing to their overall decoding delay characteristics.

KW - cs.IT

KW - cs.MM

KW - cs.PF

KW - math.IT

M3 - Conference Contribution (Conference Proceeding)

BT - IEEE ICC 2015 - Communication Theory Symposium

ER -

Binary Systematic Network Coding for Progressive Packet Decoding

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