Network Coding Capacity Regions via Entropy Functions
In this paper, we use entropy functions to characterize the set of rate-capacity tuples achievable with either zero decoding error, or vanishing decoding error, for general network coding problems for acyclic networks. We show that when sources are colocated, the outer bound is tight and the sets of...
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Published in | IEEE transactions on information theory Vol. 60; no. 9; pp. 5347 - 5374 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York, NY
IEEE
01.09.2014
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.2014.2334291 |
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Abstract | In this paper, we use entropy functions to characterize the set of rate-capacity tuples achievable with either zero decoding error, or vanishing decoding error, for general network coding problems for acyclic networks. We show that when sources are colocated, the outer bound is tight and the sets of zero-error achievable and vanishing-error achievable rate-capacity tuples are the same. Then, we extend this paper to networks subject to linear encoding constraints, routing constraints (where some or all nodes can only perform routing), and secrecy constraints. Finally, we show that even for apparently simple networks, design of optimal codes may be difficult. In particular, we prove that for the incremental multicast problem and for the single-source secure network coding problem, characterization of the achievable set can be very hard and linear network codes may not be optimal. |
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AbstractList | In this paper, we use entropy functions to characterize the set of rate-capacity tuples achievable with either zero decoding error, or vanishing decoding error, for general network coding problems for acyclic networks. We show that when sources are colocated, the outer bound is tight and the sets of zero-error achievable and vanishing-error achievable rate-capacity tuples are the same. Then, we extend this paper to networks subject to linear encoding constraints, routing constraints (where some or all nodes can only perform routing), and secrecy constraints. Finally, we show that even for apparently simple networks, design of optimal codes may be difficult. In particular, we prove that for the incremental multicast problem and for the single-source secure network coding problem, characterization of the achievable set can be very hard and linear network codes may not be optimal. |
Author | Chan, Terence H. Grant, Alex |
Author_xml | – sequence: 1 givenname: Terence H. surname: Chan fullname: Chan, Terence H. email: terence.chan@unisa.edu.au organization: Inst. for Telecommun. Res., Univ. of South Australia, Adelaide, SA, Australia – sequence: 2 givenname: Alex surname: Grant fullname: Grant, Alex email: alex.grant@unisa.edu.au organization: Inst. for Telecommun. Res., Univ. of South Australia, Adelaide, SA, Australia |
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Keywords | Network coding achievable rate regions linearity constraint incremental multicast Packet switching Source coding Error rate Routing Entropy Decoding Data broadcast Information dissemination Multicast Linear code Linear coding Linearity Optimal code Secrecy |
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SubjectTerms | Applied sciences Coding, codes Decoding Encoding Entropy Error correction & detection Error probability Exact sciences and technology Indexes Information theory Information, signal and communications theory Linear codes Network coding Random variables Routing Secret Signal and communications theory Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) |
Title | Network Coding Capacity Regions via Entropy Functions |
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