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Abstract
Despite their high computational complexity, Random Linear Network Coding (RLNC) techniques have been shown to offer a good robustness against packet erasure wireless channels. Some approaches have been recently proposed to reduce such computational burden, for both encoder and decoder elements. One of those are the so-called Tunable Sparse Network Coding (TSNC) techniques, which advocate limiting the number of packets that are combined to build a coded packet. They also propose dynamically adapting the corresponding sparsity level, as the transmission evolves, although an optimum tuning policy has not been yet found. In this paper we present a TSNC implementation that exploits a novel analytical model to estimate the probability of generating an innovative packet (linearly independent combination), given the current status at the decoder. Taking advantage of the model's accuracy, the proposed scheme offers a better trade-off between computational complexity and network performance. Furthermore, we broaden the analysis of TSNC techniques by thoroughly assessing their behavior over wireless networks using the ns-3 platform. The results yield a remarkable complexity reduction (approx. 3.33x less complexity), without jeopardizing network performance.
Original language | English |
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Title of host publication | 2017 IEEE Wireless Communications and Networking Conference (WCNC) |
Number of pages | 6 |
Publisher | IEEE |
Publication date | 10 May 2017 |
Article number | 7925561 |
ISBN (Electronic) | 978-1-5090-4183-1 |
DOIs | |
Publication status | Published - 10 May 2017 |
Event | 2017 IEEE Wireless Communications and Networking Conference, WCNC 2017 - San Francisco, United States Duration: 19 Mar 2017 → 22 Mar 2017 |
Conference
Conference | 2017 IEEE Wireless Communications and Networking Conference, WCNC 2017 |
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Country/Territory | United States |
City | San Francisco |
Period | 19/03/2017 → 22/03/2017 |
Series | I E E E Wireless Communications and Networking Conference. Proceedings |
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ISSN | 1525-3511 |
Keywords
- Network coding
- Random Linear Coding
- Sparse coding
Fingerprint
Dive into the research topics of 'How to Tune Sparse Network Coding over Wireless Links'. Together they form a unique fingerprint.Projects
- 1 Finished
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TuneSCode: TuneSCode – Tunable Sparse Network Coding for Wireless Networks
Lucani Rötter, D. E. & Sørensen, C. W.
01/09/2013 → 31/08/2016
Project: Research