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Lossless Data Compression with Side Information: Nonasymptotics and Dispersion

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Gavalakis, L 
Kontoyiannis, Ioannis  ORCID logo


The problem of lossless data compression with side information available to both the encoder and the decoder is considered. The finite-blocklength fundamental limits of the best achievable performance are defined, in two different versions of the problem: Reference-based compression, when a single side information string is used repeatedly in compressing different source messages, and pair-based compression, where a different side information string is used for each source message. General achievability and converse theorems are established. Nonasymptotic normal approximation expansions are proved for the optimal rate with memoryless sources, in both the reference-based and pair-based settings. These are stated in terms of explicit, finite-blocklength bounds, that are tight up to third-order terms. Extensions that go significantly beyond the class of memoryless sources are obtained. The relevant source dispersion is identified and its relationship with the conditional varentropy rate is established. Interestingly, the dispersion is different in reference-based and pair-based compression, and it is proved that the reference-based dispersion is in general smaller.



46 Information and Computing Sciences, 4006 Communications Engineering, 40 Engineering

Journal Title

IEEE International Symposium on Information Theory - Proceedings

Conference Name

2020 IEEE International Symposium on Information Theory (ISIT)

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