MMSE interference in Gaussian channels.

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Abstract

We consider the scalar Gaussian channel, and address the problem of maximizing the
average mutual information of a power constraint n component (n → ∞) input
random vector at a given signal-to-noise ratio (snr), satisfying a minimum mean
square error (MMSE) constraint at another lower snr value. We use the MMSE as an
effective interference (disturbance) measure, motivated by interference networks,
where codes are expected not only to optimize performance for the intended user but
inflict minimum interference on other users. We show via the information-estimation
relation, that superposition coding is optimal in this respect, providing further
intuition to the effectiveness of the Han-Kobayashi coding strategy on the interference
channel, and performance of ’bad’ codes.
Moreover, the MMSE function of those codes, attaining the best rate at some snr,
subjected to a prescribed MMSE demand at some other snr, is completely defined for
all snr, and is the one obtained by the corresponding superposition codebooks.
Extensions to two MMSE constraints, are discussed, and compared to the results for a
mutual information disturbance measure. Some challenges for this class of interference
problems will also be discussed.
Original languageEnglish
Title of host publication2012 Information Theory and Applications Workshop
Pages78-114
DOIs
StatePublished - 2012
Event2012 Information Theory and Applications Workshop - ITA
Duration: 5 Feb 201210 Feb 2012
https://ieeexplore.ieee.org/xpl/conhome/6176383/proceeding

Conference

Conference2012 Information Theory and Applications Workshop
Period5/02/1210/02/12
Internet address

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