Communication versus Computation: Duality for multiple access channels and source coding

TL;DR

This paper explores the duality between codes optimized for computation and those for source recovery in network information theory, revealing how improvements in one can affect the other.

Contribution

It establishes duality results linking computation-optimized codes with codes for multiple access and source coding, highlighting their interdependence.

Findings

Good computation codes can hinder source recovery capabilities.

Duality between computation and source coding codes is formally established.

Implications for designing network codes balancing computation and source recovery.

Abstract

Computation codes in network information theory are designed for the scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. K\"orner and Marton showed for distributed source coding that such function decoding can be achieved more efficiently than decoding the full information sources. Compute-and-forward has shown that function decoding, in combination with network coding ideas, is a useful building block for end-to-end communication. In both cases, good computation codes are the key component in the coding schemes. In this work, we expose the fact that good computation codes could undermine the capability of the codes for recovering the information sources individually, e.g., for the purpose of multiple access and distributed source coding. Particularly, we establish duality results between the codes which are good for computation and the codes which are good for multiple access or distributed compression.