Coding for Errors and Erasures in Random Network Coding

The problem of error-control in random linear network coding is considered. A ldquononcoherentrdquo or ldquochannel obliviousrdquo model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear networ...

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Bibliographic Details
Published inIEEE transactions on information theory Vol. 54; no. 8; pp. 3579 - 3591
Main Authors Koetter, R., Kschischang, F.R.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.08.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0018-9448
1557-9654
DOI10.1109/TIT.2008.926449

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Abstract The problem of error-control in random linear network coding is considered. A ldquononcoherentrdquo or ldquochannel obliviousrdquo model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear network coding is vector-space preserving, information transmission is modeled as the injection into the network of a basis for a vector space V and the collection by the receiver of a basis for a vector space U . A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum-distance decoder for this metric achieves correct decoding if the dimension of the space V cap U is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style ldquolist-1rdquo minimum-distance decoding algorithm is provided.
AbstractList The problem of error-control in random linear network coding is considered. A "noncoherent" or "channel oblivious" model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear network coding is vector-space preserving, information transmission is modeled as the injection into the network of a basis for a vector space $V$ and the collection by the receiver of a basis for a vector space $U$. A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum-distance decoder for this metric achieves correct decoding if the dimension of the space $V cap U$ is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the Singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style "list-1" minimum-distance decoding algorithm is provided. [PUBLICATION ABSTRACT]
The problem of error-control in random linear network coding is considered. A "noncoherent" or "channel oblivious" model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear network coding is vector-space preserving, information transmission is modeled as the injection into the network of a basis for a vector space V and the collection by the receiver of a basis for a vector space U. A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum-distance decoder for this metric achieves correct decoding if the dimension of the space V capU is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style "list-1" minimum-distance decoding algorithm is provided.
The problem of error-control in random linear network coding is considered. A ldquononcoherentrdquo or ldquochannel obliviousrdquo model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear network coding is vector-space preserving, information transmission is modeled as the injection into the network of a basis for a vector space (V) and the collection by the receiver of a basis for a vector space (U). A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum- distance decoder for this metric achieves correct decoding if the dimension of the space (V) cap(U) is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style ldquolist-1rdquo minimum- distance decoding algorithm is provided.
Author Kschischang, F.R.
Koetter, R.
Author_xml – sequence: 1
  givenname: R.
  surname: Koetter
  fullname: Koetter, R.
  organization: Inst. for Commun. Eng., Tech. Univ. of Munich, Munich
– sequence: 2
  givenname: F.R.
  surname: Kschischang
  fullname: Kschischang, F.R.
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20528704$$DView record in Pascal Francis
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Cites_doi 10.1006/jcta.2001.3188
10.1109/ISIT.2007.4557281
10.1007/978-3-642-74341-2
10.1109/PROC.1980.11696
10.1017/CBO9780511808968
10.1017/CBO9780511987045
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10.1109/18.978730
10.1109/ITWITWN.2007.4318069
10.1109/ISIT.2003.1228459
10.1007/BF01230125
10.1137/0518015
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Issue 8
Keywords Reed Solomon code
Finite field
Parameter estimation
sub- space metric
Coding errors
Transfer characteristic
Transmitter
Decoding
Geometrical projection
Random coding
Algorithm
Information transmission
network error correction
Linear coding
Vector space
Channel estimation
Network coding
Minimal distance
Metric
Error correction
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References ref13
ref12
ref15
ref14
mceliece (ref29) 2005
ref11
ref10
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ref16
gabidulin (ref18) 1985; 21
chou (ref2) 2003
mceliece (ref28) 2003
cai (ref7) 2006; 6
berlekamp (ref24) 1968
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References_xml – ident: ref15
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– ident: ref10
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– ident: ref21
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Snippet The problem of error-control in random linear network coding is considered. A ldquononcoherentrdquo or ldquochannel obliviousrdquo model is assumed where...
The problem of error-control in random linear network coding is considered. A "noncoherent" or "channel oblivious" model is assumed where neither transmitter...
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SubjectTerms Algorithms
Applied sciences
Codes
Coding
Coding, codes
Construction
Context modeling
Cryptography
Data encryption
Decoding
Detection, estimation, filtering, equalization, prediction
Error correction
Error correction codes
Errors
Exact sciences and technology
Geometry
Information theory
Information, signal and communications theory
Jamming
Mathematical models
Network coding
network error correction
Networks
Receivers
Signal and communications theory
Signal, noise
Strontium
subspace metric
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Transmitters
Vector spaces
Vectors
Title Coding for Errors and Erasures in Random Network Coding
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