Dynamic information and constraints in source and channel coding
Abstract
This thesis explore dynamics in source coding and channel coding.
We begin by introducing the idea of distortion side information, which does not directly depend on the source but instead affects the distortion measure. Such distortion side information is not only useful at the encoder but under certain conditions knowing it at the encoder is optimal and knowing it at the decoder is useless. Thus distortion side information is a natural complement to Wyner-Ziv side information and may be useful in exploiting properties of the human perceptual system as well as in sensor or control applications. In addition to developing the theoretical limits of source coding with distortion side information, we also construct practical quantizers based on lattices and codes on graphs. Our use of codes on graphs is also of independent interest since it highlights some issues in translating the success of turbo and LDPC codes into the realm of source coding.
Finally, to explore the dynamics of side information correlated with the source, we consider fixed lag side information at the decoder. We focus on the special case of perfect side information with unit lag corresponding to source coding with feedforward (the dual of channel coding with feedback). Using duality, we develop a linear complexity algorithm which exploits the feedforward information to achieve the rate-distortion bound.
The second part of the thesis focuses on channel dynamics in communication by introducing a new system model…
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