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Poisson channel with binary Markov input and average sojourn time constraint

Sinzger, Mark ; Gehri, Maximilian ; Koeppl, Heinz (2022):
Poisson channel with binary Markov input and average sojourn time constraint. (Postprint)
In: 2020 IEEE International Symposium on Information Theory: Proceedings, pp. 2873-2878,
Darmstadt, IEEE, ISIT'20 - International Symposium on Information Theory, Online, 21.-26.06.2020, ISSN 2157-8095, e-ISSN 2157-8117, ISBN 978-1-7281-6432-8,
DOI: 10.26083/tuprints-00021525,
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Item Type: Conference or Workshop Item
Origin: Secondary publication service
Status: Postprint
Title: Poisson channel with binary Markov input and average sojourn time constraint
Language: English
Abstract:

A minimal model for gene expression, consisting of a switchable promoter together with the resulting messenger RNA, is equivalent to a Poisson channel with a binary Markovian input process. Determining its capacity is an optimization problem with respect to two parameters: the average sojourn times of the promoter’s active (ON) and inactive (OFF) state. An expression for the mutual information is found by solving the associated filtering problem analytically on the level of distributions. For fixed peak power, three bandwidth-like constraints are imposed by lower-bounding (i) the average sojourn times (ii) the autocorrelation time and (iii) the average time until a transition. OFFfavoring optima are found for all three constraints, as commonly encountered for the Poisson channel. In addition, constraint (i) exhibits a region that favors the ON state, and (iii) shows ONfavoring local optima.

Book Title: 2020 IEEE International Symposium on Information Theory: Proceedings
Place of Publication: Darmstadt
Publisher: IEEE
Alternative keywords:
Alternative keywordsLanguage
Poisson channel, gene expression, binary Markov, average sojourn time, filtering, bandwidth constraintEnglish
Classification DDC: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Interdisziplinäre Forschungsprojekte > Centre for Synthetic Biology
Event Title: ISIT'20 - International Symposium on Information Theory
Event Location: Online
Event Dates: 21.-26.06.2020
Date Deposited: 03 Apr 2020 12:28
Last Modified: 20 Jul 2022 13:52
DOI: 10.26083/tuprints-00021525
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-215259
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21525
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