Exact Decoding Probability Under Random Linear Network Coding

In this letter, we compute the exact probability that a receiver obtains N linearly independent packets among K ≥ N received packets, when the sender/s use/s random linear network coding over a Galois Field of size q. Such condition maps to the receiver's capability to decode the original infor...

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Veröffentlicht in:	IEEE communications letters Jg. 15; H. 1; S. 67 - 69
Hauptverfasser:	Trullols-Cruces, O, Barcelo-Ordinas, J M, Fiore, M
Format:	Journal Article Verlag
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.01.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Coding Coding, codes Computer networks Computer Science Computer simulation Decoding Encoding Enginyeria de la telecomunicació error control Exact sciences and technology Galois fields Implementació Information, signal and communications theory Mathematical analysis Mathematical models Network coding Networking and Internet Architecture Networks Random linear network coding Receivers Signal and communications theory Telecommunications and information theory Telemàtica i xarxes d'ordinadors Upper bound Vectors Wireless communication systems wireless networks Xarxes sense fils Àrees temàtiques de la UPC Finite field Upper bound Linear coding Grounding Wireless telecommunication error control Wireless network wireless networks Decoding Random coding Random linear network coding
ISSN:	1089-7798, 1558-2558
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Beschreibung
Zusammenfassung:	In this letter, we compute the exact probability that a receiver obtains N linearly independent packets among K ≥ N received packets, when the sender/s use/s random linear network coding over a Galois Field of size q. Such condition maps to the receiver's capability to decode the original information, and its mathematical characterization helps to design the coding so to guarantee the correctness of the transmission. Our formulation represents an improvement over the current upper bound for the decoding probability, and provides theoretical grounding to simulative results in the literature.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	1089-7798 1558-2558
DOI:	10.1109/LCOMM.2010.110310.101480