Conditional entropy and error probability

Fano´s inequality relates the error probability and conditional entropy of a finitely-valued random variable X given another random variable Y. It is not necessarily tight when the marginal distribution of X is fixed. In this paper, we consider both finite and countably infinite alphabets. A tight upper bound on the conditional entropy of X given Y is given in terms of the error probability and the marginal distribution of X. A new lower bound on the conditional entropy for countably infinite alphabet is also found. The equivalence of the reliability criteria of vanishing error probability and vanishing conditional entropy is established in wide generality.