A Proof of the Generalized Markov Lemma with Countable Infinite Sources

Abstract

The Generalized Markov Lemma has been used in the proofs of several multiterminal source coding theorems for finite alphabets. An alternative approach to extend this result to countable infinite sources is proposed. We establish sufficient conditions to guarantee the joint typicality of reproduction sequences of random descriptions that have not been necessarily generated from the product of probability measures. Compared to the existing proofs for finite alphabets, our technique is simpler and self-contained. It also offers bounds on the asymptotic tail probability of the typicality event providing a scaling law for a large number of source encoders.