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On the Capacity of a Class of Signal-Dependent Noise Channels
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran..
Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
Sharif Univ Technol, Dept Elect Engn, Tehran 11155, Iran.;Sharif Univ Technol, Adv Commun Res Inst, Tehran 11155, Iran..
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2018 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 64, no 12, p. 7828-7846Article in journal (Refereed) Published
Abstract [en]

In some applications, the variance of additive measurement noise depends on the signal that we aim to measure. For instance, additive signal-dependent Gaussian noise (ASDGN) channel models are used in molecular and optical communication. Herein, we provide lower and upper bounds on the capacity of additive signal-dependent noise (ASDN) channels. The first lower bound is based on an extension of majorization inequalities, and the second lower bound utilizes the properties of the differential entropy. The lower bounds are valid for arbitrary ASDN channels. The upper bound is based on a previous idea of the authors ("symmetric relative entropy") and is applied to the ASDGN channels. These bounds indicate that in the ASDN channels (unlike the classical additive white Gaussian noise channels), the capacity does not necessarily become larger by reducing the noise variance function. We also provide sufficient conditions under which the capacity becomes infinite. This is complemented by some conditions implying that the capacity is finite, and a unique capacity achieving measure exists (in the sense of the output measure).

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 64, no 12, p. 7828-7846
Keywords [en]
Signal-dependent noise channels, molecular communication, channels with infinite capacity, existence of capacity-achieving distribution
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-239975DOI: 10.1109/TIT.2018.2867599ISI: 000451257100021Scopus ID: 2-s2.0-85052638174OAI: oai:DiVA.org:kth-239975DiVA, id: diva2:1269690
Note

QC 20181211

Available from: 2018-12-11 Created: 2018-12-11 Last updated: 2018-12-11Bibliographically approved

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