Networking

Relative Entropy at the Channel Output of a Capacity-Achieving Code

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Executive Summary

In this paper the authors establish a new inequality tying together the coding rate, the probability of error and the relative entropy between the channel and the auxiliary output distribution. This inequality is then used to show the strong converse, and to prove that the output distribution of a code must be close, in relative entropy, to the capacity achieving output distribution (for DMC and AWGN). One of the key tools in their analysis is the concentration of measure (isoperimetry).

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