Optimality and Approximate Optimality of Source-Channel Separation in Networks

TL;DR

This paper analyzes the optimality of source-channel separation in communication networks, showing it is optimal in two scenarios and approximately optimal in a third, with implications for network design and coding strategies.

Contribution

It identifies conditions under which source-channel separation is optimal or near-optimal in complex network scenarios, extending classical results to more general settings.

Findings

Separation is optimal for synchronized, orthogonal, memoryless channels with correlated sources.

Separation remains optimal for independent sources with general multi-user channels.

Approximate optimality is demonstrated for scenarios with multiple destinations and different distortions, with bounds on the loss.

Abstract

We consider the source-channel separation architecture for lossy source coding in communication networks. It is shown that the separation approach is optimal in two general scenarios, and is approximately optimal in a third scenario. The two scenarios for which separation is optimal complement each other: the first is when the memoryless sources at source nodes are arbitrarily correlated, each of which is to be reconstructed at possibly multiple destinations within certain distortions, but the channels in this network are synchronized, orthogonal and memoryless point-to-point channels; the second is when the memoryless sources are mutually independent, each of which is to be reconstructed only at one destination within a certain distortion, but the channels are general, including multi-user channels such as multiple access, broadcast, interference and relay channels, possibly with feedback. The third scenario, for which we demonstrate approximate optimality of source-channel separation, generalizes the second scenario by allowing each source to be reconstructed at multiple destinations with different distortions. For this case, the loss from optimality by using the separation approach can be upper-bounded when a "difference" distortion measure is taken, and in the special case of quadratic distortion measure, this leads to universal constant bounds.