A Generalization of the DMC

TL;DR

This paper extends the discrete memoryless channel model by introducing a cloud-based output distribution, deriving error exponents, capacity, and bounds for this generalized channel ensemble.

Contribution

It presents a novel generalization of the DMC with a cloud-based output distribution and derives fundamental limits like error exponents and capacity for this model.

Findings

Derived achievable error exponent for the generalized channel

Established converse bounds and optimal decoding exponents

Obtained the capacity of the channel ensemble

Abstract

We consider a generalization of the discrete memoryless channel, in which the channel probability distribution is replaced by a uniform distribution over clouds of channel output sequences. For a random ensemble of such channels, we derive an achievable error exponent, as well as its converse together with the optimal correct-decoding exponent, all as functions of information rate. As a corollary of these results, we obtain the channel ensemble capacity.