Universal Decoding for Asynchronous Slepian-Wolf Encoding

We consider the problem of (almost) lossless source coding of two correlated memoryless sources using separate encoders and a joint decoder, that is, Slepian-Wolf (S-W) coding. In our setting, the encoding and decoding are asynchronous, i.e., there is a certain relative delay between the two sources. Neither the source parameters nor the relative delay are known to the encoders and the decoder. Since we assume that both encoders implement standard random binning, which does not require such knowledge anyway, the focus of this work is on the decoder. Our main contribution is in proposing a universal decoder, that independent of the unknown source parameters and the relative delay, and at the same time, is asymptotically as good as the optimal maximum a posteriori probability (MAP) decoder in the sense of the random coding error exponent achieved. Consequently, the achievable rate region is also the same as if the source parameters and the delay were known to the decoder.

[1]  Dominique de Caen,et al.  A lower bound on the probability of a union , 1997, Discret. Math..

[2]  Neri Merhav,et al.  Optimum Tradeoffs Between the Error Exponent and the Excess-Rate Exponent of Variable-Rate Slepian–Wolf Coding , 2015, IEEE Transactions on Information Theory.

[3]  Uyematsu Tomohiko,et al.  Universal Coding for Asynchronous Slepian-Wolf Coding Systems , 2013 .

[4]  Frans M. J. Willems Totally asynchronous Slepian-Wolf data compression , 1988, IEEE Trans. Inf. Theory.

[5]  Imre Csiszár,et al.  Information Theory - Coding Theorems for Discrete Memoryless Systems, Second Edition , 2011 .

[6]  Abraham Lempel,et al.  Compression of individual sequences via variable-rate coding , 1978, IEEE Trans. Inf. Theory.

[7]  Imre Csiszár,et al.  Towards a general theory of source networks , 1980, IEEE Trans. Inf. Theory.

[8]  Meir Feder,et al.  Universal Decoding for Channels with Memory , 1998, IEEE Trans. Inf. Theory.

[9]  Meir Feder,et al.  Communication over Individual Channels -- a general framework , 2012, ArXiv.

[10]  Tomohiko Uyematsu,et al.  Coding Theorems for Asynchronous Slepian–Wolf Coding Systems , 2019, IEEE Transactions on Information Theory.

[11]  Imre Csiszár Linear codes for sources and source networks: Error exponents, universal coding , 1982, IEEE Trans. Inf. Theory.

[12]  Tomohiko Uyematsu,et al.  Achievable rate regions for asynchronous Slepian-Wolf coding systems , 2015, 2015 IEEE Information Theory Workshop - Fall (ITW).

[13]  R. Urbanke,et al.  Asynchronous Slepian-Wolf coding via source-splitting , 1997, Proceedings of IEEE International Symposium on Information Theory.

[14]  Chao Tian,et al.  LDPC code design for asynchronous Slepian-Wolf coding , 2010, IEEE Transactions on Communications.

[15]  Tsachy Weissman,et al.  The porosity of additive noise sequences , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[16]  Neri Merhav Universal decoding for memoryless Gaussian channels with a deterministic interference , 1993, IEEE Trans. Inf. Theory.

[17]  Neri Merhav Universal Decoding Using a Noisy Codebook , 2018, IEEE Transactions on Information Theory.

[18]  Meir Feder,et al.  Universal Communication—Part I: Modulo Additive Channels , 2013, IEEE Transactions on Information Theory.

[19]  Te Sun Han,et al.  Universal coding for the Slepian-Wolf data compression system and the strong converse theorem , 1994, IEEE Trans. Inf. Theory.

[20]  Jun Chen,et al.  On Universal Variable-Rate Slepian-Wolf Coding , 2008, 2008 IEEE International Conference on Communications.

[21]  S. Sarvotham,et al.  Variable-Rate Universal Slepian-Wolf Coding with Feedback , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[22]  Neri Merhav,et al.  Universal composite hypothesis testing: A competitive minimax approach , 2002, IEEE Trans. Inf. Theory.

[23]  Jacob Ziv,et al.  Universal decoding for finite-state channels , 1985, IEEE Trans. Inf. Theory.

[24]  Neri Merhav Universal decoding for source-channel coding with side information , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[25]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[26]  John C. Kieffer,et al.  Some Universal Noiseless Multiterminal Source Coding Theorems , 1980, Inf. Control..

[27]  Amos Lapidoth,et al.  On the Universality of the LZ-Based Decoding Algorithm , 1998, IEEE Trans. Inf. Theory.

[28]  Stark C. Draper Universal Incremental Slepian-Wolf Coding , 2004 .