Communication Versus Computation: Duality for Multiple-Access Channels and Source Coding
Jingge Zhu, Sung Hoon Lim, Michael Gastpar · IEEE Transactions on Information Theory · 2018
Computation codes in network information theory are designed for scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. Körner and Marton showed for distributed source coding (DSC) that such function decoding can be achieved more efficiently than decoding the full information sources. Compute-forward has shown that function decoding, in combination with network coding ideas, is a useful building block for end-to-end communication over a network. In both cases, good computation codes are the key component in the coding schemes. Could these same codes simultaneously also enable full message decoding over a sufficiently strong multiple-access channel (MAC)? This work establishes a partial negative answer and converse result. Specifically, for any code that is known to be a good computation code for some MAC, we characterize a class of MACs for which that code cannot enable full message decoding (and vice versa). Finally, an analogous duality result is established for a related DSC problem.