Achieving Csiszár's source-channel coding exponent with product distributions

We derive a random-coding upper bound on the average probability of error of joint source-channel coding that recovers Csiszár's error exponent when used with product distributions over the channel inputs. Our proof technique for the error probability analysis employs a code construction for which source messages are assigned to subsets and codewords are generated with a distribution that depends on the subset. © 2012 IEEE.

Three dimensional distributions of arsenic and platinum within NiSi contact and gate of an n-type transistor

Atom probe tomography was used to study the redistribution of platinum and arsenic atoms after Ni(Pt) silicidation of As-doped polycrystalline Si. These measurements were performed on a field-effect transistor and compared with those obtained in unpatterned region submitted to the same process. These results suggest that Pt and As redistribution during silicide formation is only marginally influenced by the confinement in microelectronic devices. On the contrary, there is a clear difference with the redistribution reported in the literature for the blanket wafers. Selective etching used to remove the non-reacted Ni(Pt) film after the first rapid heat treatment may induce this difference. © 2011 American Institute of Physics.

A derivation of the source-channel error exponent using nonidentical product distributions

This paper studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred to as classes), and codewords are independently generated according to a distribution that depends on the class index of the source message. For discrete memoryless systems, two optimally chosen classes and product distributions are found to be sufficient to attain the sphere-packing exponent in those cases where it is tight. © 2014 IEEE.