Lossless Coding for Distributed Streaming Sources

Distributed source coding is traditionally viewed in a block coding context wherein all source symbols are known in advance by the encoders. However, many modern applications to which distributed source coding ideas are applied, are better modeled as having streaming data. In a streaming setting, so...

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Veröffentlicht in:IEEE transactions on information theory Jg. 60; H. 3; S. 1447 - 1474
Hauptverfasser: Draper, Stark C., Cheng Chang, Sahai, Anant
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.03.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9448, 1557-9654
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Abstract Distributed source coding is traditionally viewed in a block coding context wherein all source symbols are known in advance by the encoders. However, many modern applications to which distributed source coding ideas are applied, are better modeled as having streaming data. In a streaming setting, source symbol pairs are revealed to separate encoders in real time and need to be reconstructed at the decoder with subject to some tolerable end-to-end delay. In this paper, a causal sequential random binning encoder is introduced and paired with maximum likelihood (ML) and universal decoders. The latter uses a novel weighted empirical suffix entropy decoding rule. We derive a lower bounds on the error exponent with delay for each decoder. We also provide upper bounds for the special case of streaming with decoder side information and discuss when upper and lower bounds match. We show that both ML and universal decoders achieve the same (positive) error exponents for all rate pairs inside the Slepian-Wolf achievable rate region. The dominant error events in streaming are different from those in block-coding and result in different exponents. Because the sequential random binning scheme is also universal over delays, the resulting code eventually reconstructs every source symbol correctly with probability one.
AbstractList Distributed source coding is traditionally viewed in a block coding context wherein all source symbols are known in advance by the encoders. However, many modern applications to which distributed source coding ideas are applied, are better modeled as having streaming data. In a streaming setting, source symbol pairs are revealed to separate encoders in real time and need to be reconstructed at the decoder with subject to some tolerable end-to-end delay. In this paper, a causal sequential random binning encoder is introduced and paired with maximum likelihood (ML) and universal decoders. The latter uses a novel weighted empirical suffix entropy decoding rule. We derive a lower bounds on the error exponent with delay for each decoder. We also provide upper bounds for the special case of streaming with decoder side information and discuss when upper and lower bounds match. We show that both ML and universal decoders achieve the same (positive) error exponents for all rate pairs inside the Slepian-Wolf achievable rate region. The dominant error events in streaming are different from those in block-coding and result in different exponents. Because the sequential random binning scheme is also universal over delays, the resulting code eventually reconstructs every source symbol correctly with probability one.
Distributed source coding is traditionally viewed in a block coding context wherein all source symbols are known in advance by the encoders. However, many modern applications to which distributed source coding ideas are applied, are better modeled as having streaming data. In a streaming setting, source symbol pairs are revealed to separate encoders in real time and need to be reconstructed at the decoder with subject to some tolerable end-to-end delay. In this paper, a causal sequential random binning encoder is introduced and paired with maximum likelihood (ML) and universal decoders. The latter uses a novel weighted empirical suffix entropy decoding rule. We derive a lower bounds on the error exponent with delay for each decoder. We also provide upper bounds for the special case of streaming with decoder side information and discuss when upper and lower bounds match. We show that both ML and universal decoders achieve the same (positive) error exponents for all rate pairs inside the Slepian-Wolf achievable rate region. The dominant error events in streaming are different from those in block-coding and result in different exponents. Because the sequential random binning scheme is also universal over delays, the resulting code eventually reconstructs every source symbol correctly with probability one. [PUBLICATION ABSTRACT]
Author Sahai, Anant
Cheng Chang
Draper, Stark C.
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Cites_doi 10.1109/TIT.2008.924691
10.1155/2009/508167
10.1109/ICME.2008.4607512
10.1002/0471200611
10.1109/TIT.1976.1055508
10.1109/CDC.2011.6161478
10.1109/TIT.2008.920339
10.1109/JPROC.2004.839619
10.1109/TIT.1973.1055037
10.1109/ISIT.2005.1523572
10.1109/TIT.2010.2040867
10.1109/TIT.2006.885500
10.1016/S0019-9958(74)90876-6
10.1145/195058.195462
10.1109/SFCS.1984.715906
10.1109/ACSSC.2005.1600071
10.1109/TIT.2009.2032803
10.1109/TIT.2003.819334
10.1109/TIT.1975.1055356
10.1017/CBO9780511804441
10.1109/TIT.2006.878169
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Issue 3
Keywords Streaming
Lower bound
Block code
Lossless circuit
streaming data
Source coding
Coding circuit
Distributed source signal
Entropy
Slepian-Wolf coding
lossless source coding
Information transmission
Maximum likelihood decoding
Distributed source coding
Upper bound
Delay time
Maximum likelihood
Causality
universal decoding
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References ref13
ref15
ref31
ref30
ref11
ref32
ref10
chang (ref2) 2007
ref1
ref17
ref19
meng (ref18) 2011
sahai (ref25) 2005
shulman (ref26) 2002
sahai (ref24) 0
ref23
girod (ref14) 2005; 93
ref22
ref21
dragotti (ref6) 2009
ref28
koshelev (ref16) 1977; 13
ref27
csisz r (ref5) 1981
draper (ref7) 2004
ref29
ref8
ref9
puri (ref20) 2002
ref4
ref3
gallager (ref12) 1976
References_xml – year: 1981
  ident: ref5
  publication-title: Information Theory Coding Theorems for Discrete Memoryless Systems
– ident: ref30
  doi: 10.1109/TIT.2008.924691
– ident: ref9
  doi: 10.1155/2009/508167
– ident: ref19
  doi: 10.1109/ICME.2008.4607512
– ident: ref4
  doi: 10.1002/0471200611
– volume: 13
  start-page: 26
  year: 1977
  ident: ref16
  article-title: On a problem of separate coding of two dependent sources
  publication-title: Prob Peredachi Inf
– ident: ref31
  doi: 10.1109/TIT.1976.1055508
– ident: ref28
  doi: 10.1109/CDC.2011.6161478
– ident: ref22
  doi: 10.1109/TIT.2008.920339
– year: 2007
  ident: ref2
  publication-title: Streaming source coding with delay
– volume: 93
  start-page: 71
  year: 2005
  ident: ref14
  article-title: Distributed video coding
  publication-title: Proc IEEE
  doi: 10.1109/JPROC.2004.839619
– ident: ref27
  doi: 10.1109/TIT.1973.1055037
– ident: ref8
  doi: 10.1109/ISIT.2005.1523572
– ident: ref32
  doi: 10.1109/TIT.2010.2040867
– ident: ref29
  doi: 10.1109/TIT.2006.885500
– year: 0
  ident: ref24
  article-title: Source coding and channel requirements for unstable processes
  publication-title: IEEE Trans Inf Theory 2006
– ident: ref11
  doi: 10.1016/S0019-9958(74)90876-6
– start-page: 538
  year: 2005
  ident: ref25
  article-title: A simple encoding and decoding strategy for stabilization over discrete memoryless channels
  publication-title: Proc Allerton Conf
– ident: ref21
  doi: 10.1145/195058.195462
– ident: ref13
  doi: 10.1109/SFCS.1984.715906
– start-page: 127
  year: 2002
  ident: ref26
  article-title: Source broadcasting with an unknown amount of receiver side information
  publication-title: Proc Inf Theory Workshop
– year: 2009
  ident: ref6
  publication-title: Distributed source coding Theory algorithms and applications
– year: 1976
  ident: ref12
  publication-title: Source coding with side information and universal coding
– start-page: 262
  year: 2002
  ident: ref20
  article-title: <formula formulatype="inline"><tex Notation="TeX">$n$</tex></formula>-channel multiple descriptions: Theory and construction
  publication-title: Proc Data Compress Conf
– ident: ref10
  doi: 10.1109/ACSSC.2005.1600071
– ident: ref15
  doi: 10.1109/TIT.2009.2032803
– ident: ref17
  doi: 10.1109/TIT.2003.819334
– start-page: 1
  year: 2011
  ident: ref18
  article-title: Tree interactive encoding and decoding: Conditionally <formula formulatype="inline"> <tex Notation="TeX">$\phi$</tex></formula>-mixing sources
  publication-title: Proc Int Symp Inf Theory
– ident: ref3
  doi: 10.1109/TIT.1975.1055356
– start-page: 1332
  year: 2004
  ident: ref7
  article-title: Universal incremental Slepian-Wolf coding
  publication-title: Proc Allerton Conf
– ident: ref1
  doi: 10.1017/CBO9780511804441
– ident: ref23
  doi: 10.1109/TIT.2006.878169
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SubjectTerms Applied sciences
Codes
Coding, codes
Delays
Distributed source coding
Entropy
Exact sciences and technology
Information theory
Information, signal and communications theory
Joints
lossless source coding
Maximum likelihood decoding
Maximum likelihood method
Probability distribution
Signal and communications theory
Slepian-Wolf coding
Source coding
streaming data
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
universal decoding
Title Lossless Coding for Distributed Streaming Sources
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