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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Published in | IEEE transactions on information theory Vol. 54; no. 8; pp. 3579 - 3591 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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 Access | Get full text |
ISSN | 0018-9448 1557-9654 |
DOI | 10.1109/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. |
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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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CODEN | IETTAW |
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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 10.4310/CIS.2006.v6.n1.a2 10.1109/TIT.2007.909139 10.1109/TIT.2008.921711 10.1109/TIT.2006.881746 10.1007/s10623-008-9221-7 10.1023/A:1008394205999 10.1109/TIT.2003.809567 10.4310/CIS.2006.v6.n1.a3 10.1007/BF01390772 10.1049/ip-com:20045307 10.1109/18.978730 10.1109/ITWITWN.2007.4318069 10.1109/ISIT.2003.1228459 10.1007/BF01230125 10.1137/0518015 |
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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 ref1 ref17 ref16 gabidulin (ref18) 1985; 21 chou (ref2) 2003 mceliece (ref28) 2003 cai (ref7) 2006; 6 berlekamp (ref24) 1968 ref23 yeung (ref6) 2006; 6 ref20 ref22 ref21 loidreau (ref19) 2006; 3969 ref27 lidl (ref26) 1983; 20 macwilliams (ref25) 1977 ref8 ref9 ref4 ref3 ref5 |
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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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