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Paper Detail

Paper IDO.3.2
Paper Title Improved Achievable Regions in Networked Scalable Coding Problems
Authors Emrah Akyol, Binghamton University, United States; Urbashi Mitra, University of Southern California, United States; Ertem Tuncel, UC Riverside, United States; Kenneth Rose, UC Santa Barbara, United States
Session O.3: Multi-terminal Source Coding I
Presentation Lecture
Track Source Coding
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract In this paper, we present new results on the achievable rate-distortion regions in networked scalable compression problems, based on a flexible codebook generation and binning method. First, we consider the problem of scalable coding in the presence of decoder side information, for which the prior work analyzed the two important cases the degraded side information where source $X$ and the side information variables ($Y_1, Y_2$) form a Markov chain in the order of either $X-Y_1-Y_2$ or $X-Y_2-Y_1$. First, we present an example non-Markov side information scenario where the proposed coding strategy achieves a strictly larger rate-distortion region compared to prior work. We then consider the problem of multi-user successive refinement where different users that are connected to a central server via links with different noiseless capacities strive to reconstruct the source in a progressive fashion. It is shown that a prior rate-distortion region is suboptimal in general, albeit its optimality for a Gaussian source with MSE distortion, and the proposed coding scheme achieves points beyond the achievable region of prior work.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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