The additive exponential noise channel with additive exponential interference (AENC-AEI) known non-causally at the transmitter is studied. This channel can be considered as an exponential version of the discrete memoryless channel with state known non-causally at the encoder considered by Gelfand and Pinsker. We make use of Gelf’and-Pinsker’s classic capacity Theorem to derive inner and outer b...

In this paper, the secrecy problem in the state dependent causal cognitive interference channel is studied. The channel state is non-causally known at the cognitive encoder. The message of the cognitive encoder must be kept secret from the primary receiver. We use a coding scheme which is a combination of compress-and-forward strategy with Marton coding, Gel’fand-Pinsker coding and Wyner’s wire...

A major consideration we had in writing this survey was to make it accessible to mathematicians as well as to computer scientists, since expander graphs, the protagonists of our story, come up in numerous and often surprising contexts in both fields. But, perhaps, we should start with a few words about graphs in general. They are, of course, one of the prime objects of study in Discrete Mathema...

New upper bounds on the relative entropy are derived as a function of the total variation distance. One bound refines an inequality by Verdú for general probability measures. A second bound improves the tightness of an inequality by Csiszár and Talata for arbitrary probability measures that are defined on a common finite set. The latter result is further extended, for probability measures on a ...

Mixture distributions are extensively used as a modeling tool in diverse areas from machine learning to communications engineering physics, and obtaining bounds on the entropy of mixture is fundamental importance many these applications. This article provides sharp concavity deficit, which difference between differential weighted sum entropies constituent components. Toward establishing lower u...