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Uncertainty quantification in molecular signals using polynomial chaos expansion
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Abbaszadeh, Mahmoud, Moutsinas, Giannis, Thomas, P. J. (Peter J.) and Guo, Weisi (2019) Uncertainty quantification in molecular signals using polynomial chaos expansion. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 4 (4). pp. 248-256. doi:10.1109/TMBMC.2019.2936349 ISSN 2332-7804.
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Official URL: http://dx.doi.org/10.1109/TMBMC.2019.2936349
Abstract
Molecular signals are abundant in engineering and biological contexts, and undergo stochastic propagation in fluid dynamic channels. The received signal is sensitive to a variety of input and channel parameter variations. Currently we do not understand how uncertainty or noise in a variety of parameters affect the received signal concentration, and nor do we have an analytical framework to tackle this challenge. In this paper we utilize Polynomial Chaos Expansion (PCE) to show that uncertainty in parameters propagates to uncertainty in the received signal. For demonstrating its applicability we consider a Turbulent Diffusion Molecular Communication (TDMC) channel and highlight which parameters affect the received signals. This can pave the way for future information theoretic insights, as well as guide experimental design.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Journal or Publication Title: | IEEE Transactions on Molecular, Biological and Multi-Scale Communications | ||||||||
Publisher: | IEEE | ||||||||
ISSN: | 2332-7804 | ||||||||
Official Date: | December 2019 | ||||||||
Dates: |
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Volume: | 4 | ||||||||
Number: | 4 | ||||||||
Page Range: | pp. 248-256 | ||||||||
DOI: | 10.1109/TMBMC.2019.2936349 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 23 October 2019 |
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