Coding theorems using Rényi information measures

Tyagi, Himanshu (2017) Coding theorems using Rényi information measures. In: 23rd National Conference on Communications, NCC 2017, 02-04 March 2017, Chennai, India, pp. 1-6.

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Abstract

We present single-shot coding theorems for standard problems in information theory and show that the results retain the form of their asymptotic counterparts, with Rényi information measures replacing the corresponding Shannon information measures. In particular, the code sizes for fixed-length lossless source codes are bounded in terms of Rényi entropy and conditional Rényi entropy; code sizes for channel coding and for lossy source coding are bounded in terms of appropriate notions of Rényi mutual information. As a corollary, we identify simple sufficient conditions for asymptotic optimal rates to not depend on the probability of error, i.e., for the strong converse property to hold, in the lossless source coding and the channel coding problems.

Item Type:	Conference Paper
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The Copyright of this article belongs to the Institute of Electrical and Electronics Engineers Inc.
Keywords:	Channel coding; Entropy; Information theory; Information measures; Lossless source coding; Lossy source coding; Mutual informations; Probability of errors; Shannon information; Standard problems; Strong converse; Codes (symbols)
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	13 Jun 2022 05:53
Last Modified:	13 Jun 2022 05:53
URI:	https://eprints.iisc.ac.in/id/eprint/73301

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