Resilient Source Coding

This paper provides a source coding theorem for multi-dimensional information signals when, at a given instant, the distribution associated with one arbitrary component of the signal to be compressed is not known and a side information is available at the destination. This new framework appears to be both of information-theoretical and game-theoretical interest: it provides a new type of constraints to compress an information source; it is useful for designing certain types of mediators in games and characterize utility regions for games with signals. Regarding the latter aspect, we apply the derived source coding theorem to the prisoner's dilemma and the battle of the sexes

On source and channel codes for multiple inputs and outputs: does multiple description beat space time?

We compare two strategies for lossy source description across a pair of unreliable channels. In the first strategy, we use a broadcast channel code to achieve a different rate for each possible channel realization, and then use a multiresolution source code to describe the source at the resulting rates. In the second strategy, we use a channel coding strategy for two independent channels coupled with a multiple description source code. In each case, we choose the coding parameters to minimize the expected end-to-end distortion in the source reconstruction. We demonstrate that in point-to-point communication across a pair of non-ergodic channels, multiple description coding can provide substantial gains relative to multiresolution and broadcast coding. We then investigate this comparison in a simple MIMO channel. We demonstrate the inferior performance of space time coding with multiresolution source coding and broadcast channel coding relative to multiple description codes and a time sharing channel coding strategy. These results indicate that for non-ergodic channels, the traditional definition of channel capacity does not necessarily lead to the best channel code from the perspective of end-to-end source distortion

Second-Order Coding Rates for Conditional Rate-Distortion

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the non-asymptotic bounds for three different scenarios: discrete memoryless sources, Gaussian sources, and Markov sources. We obtain the second-order coding rates for these settings. It is interesting to observe that the second-order coding rate for Gaussian source coding with Gaussian side information available at both the encoder and the decoder is the same as that for Gaussian source coding without side information. Furthermore, regardless of the variance of the side information, the dispersion is $1/2$ nats squared per source symbol.Comment: 20 pages, 2 figures, second-order coding rates, finite blocklength, network information theor

Successive Wyner-Ziv Coding Scheme and its Application to the Quadratic Gaussian CEO Problem

We introduce a distributed source coding scheme called successive Wyner-Ziv coding. We show that any point in the rate region of the quadratic Gaussian CEO problem can be achieved via the successive Wyner-Ziv coding. The concept of successive refinement in the single source coding is generalized to the distributed source coding scenario, which we refer to as distributed successive refinement. For the quadratic Gaussian CEO problem, we establish a necessary and sufficient condition for distributed successive refinement, where the successive Wyner-Ziv coding scheme plays an important role.Comment: 28 pages, submitted to the IEEE Transactions on Information Theor

Source Coding for a Multihop Network

Summary form only given. In this paper, we bound the rate-distortion region for a four-node network. The results are the first known expansion of rate-distortion theory from single-hop networks (every source has a direct connection to each of its destinations), to multihop networks, which allow intermediate nodes. While single-hop network source coding solutions may be applied in multihop networks, such applications require explicit rate allocation for each source-destination pair, and the resulting solutions may be suboptimal. We therefore tackle the multihop network source coding problem directly using a diamond network