Source Coding Problems with Conditionally Less Noisy Side Information

Roy Timo

Institute for Telecommunications Research
Adelaide, Australia

Abstract:

A computable characterisation of the rate-distortion (RD) function proposed by Heegard and Berger has eluded information theory for nearly three decades. Heegard and Berger's single-letter achievability bound is well known to be optimal for degraded side information; however, it is not known whether the bound is optimal for arbitrarily correlated side information (general discrete memoryless sources). In this talk, we consider a new setup in which the side information at one receiver is `conditionally less noisy' than the side information at the other. The new setup includes degraded side information as a special case, and it is motivated by the literature on degraded and less noisy broadcast channels. Our key contribution is a converse proving the optimality of Heegard and Berger's achievability bound in a new setting. The converse rests upon a certain entropy characterisation problem, which we solve using an information theoretic telescoping identity recently presented by Kramer. We also generalise the above ideas to certain three-stage successive refinement and scalable source coding problems.

Biography:

Roy Timo is a research fellow with the Institute for Telecommunications Research in Adelaide, Australia. He received the Bachelor of Engineering and Ph.D. degrees from The Australian National University in July 2005 and December 2009 respectively. He is currently a visiting postdoctoral research associate in the Department of Electrical Engineering at Princeton University. He is a member of IEEE and the Information Theory Society. His research interests include source coding and multi-terminal information theory.