Skip to main content

On communications through a Gaussian noise channel with an MMSE disturbance constraint

Author(s): Dytso, Alex; Bustin, Ronit; Tuninetti, Daniela; Devroye, Natasha; Poor, H Vincent; et al

To refer to this page use:
Abstract: This paper considers a Gaussian channel with one transmitter and two receivers. The goal is to maximize the communication rate at the intended/primary receiver subject to a disturbance constraint at the unintended/secondary receiver. The disturbance is measured in terms of minimum mean square error (MMSE) of the interference that the transmission to the primary receiver inflicts on the secondary receiver. The paper presents a new upper bound for the problem of maximizing the mutual information subject to an MMSE constraint. The new bound holds for vector inputs of any length and recovers a previously known limiting (when the length for vector input tends to infinity) expression from the work of Bustin et al. The key technical novelty is a new upper bound on MMSE. This new bound allows one to bound the MMSE for all signal-to-noise ratio (SNR) values below a certain SNR at which the MMSE is known (which corresponds to the disturbance constraint). This new bound complements the ‘single-crossing point property’ of the MMSE that upper bounds the MMSE for all SNR values above a certain value at which the MMSE value is known. The new MMSE upper bound provides a refined characterization of the phase-transition phenomenon which manifests, in the limit as the length of the vector input goes to infinity, as a discontinuity of the MMSE for the problem at hand. A matching lower bound, to within an additive gap of order O (log log 1/MMSE) (where MMSE is the disturbance constraint), is shown by means of the mixed inputs recently introduced by Dytso et al.
Publication Date: 30-Mar-2017
Citation: Dytso, Alex, Bustin, Ronit, Tuninetti, Daniela, Devroye, Natasha, Poor, H Vincent, Shamai Shitz, Shlomo. (2016). On communications through a Gaussian noise channel with an MMSE disturbance constraint. 2016 Information Theory and Applications Workshop (ITA), 10.1109/ita.2016.7888177
DOI: doi:10.1109/ita.2016.7888177
Type of Material: Conference Article
Journal/Proceeding Title: 2016 Information Theory and Applications Workshop (ITA)
Version: Author's manuscript

Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.