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Optimal Decoding and Performance analysis of a Noisy Channel Network with Network Coding
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-5407-0835
Chalmers University of Technology.
2009 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 57, no 5, 1402-1412 p.Article in journal (Refereed) Published
Abstract [en]

We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks).With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding.

Place, publisher, year, edition, pages
IEEE , 2009. Vol. 57, no 5, 1402-1412 p.
Keyword [en]
Application software, Channel coding, Computer networks, Error probability, IP networks, Maximum likelihood decoding, Network coding, Performance analysis, Signal to noise ratio, Spine
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-45809DOI: 10.1109/TCOMM.2009.05.070201ISI: 000266069700029ScopusID: 2-s2.0-66949170647OAI: diva2:452944
VR Project
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111101. Updated from conference paper to articleAvailable from: 2011-11-01 Created: 2011-10-31 Last updated: 2011-12-08Bibliographically approved

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