Optimality and approximate optimality of source-channel separation in networks

Chao Tian, Jun Chen, Suhas N. Diggavi, Shlomo Shamai

Research output: Contribution to journalArticlepeer-review


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 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.

Original languageEnglish
Article number6671968
Pages (from-to)904-918
Number of pages15
JournalIEEE Transactions on Information Theory
Issue number2
StatePublished - Feb 2014


  • Joint source-channel coding
  • separation

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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