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Molecular information delivery in porous media
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Fang, Yuting, Guo, Weisi, Icardi, Matteo, Noel, Adam and Yang, Nan (2019) Molecular information delivery in porous media. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, 4 (4). pp. 257-262. doi:10.1109/TMBMC.2019.2937297 ISSN 2372-2061.
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WRAP-molecular-information-delivery-porous-media-Noel-2019.pdf - Accepted Version - Requires a PDF viewer. Download (1310Kb) | Preview |
Official URL: https://doi.org/10.1109/TMBMC.2019.2937297
Abstract
Information delivery via molecular signals is abundant in nature and potentially useful for industry sensing. Many propagation channels (e.g., tissue membranes and catalyst beds) contain porous medium materials and the impact this has on communication performance is not well understood. Here, communication through realistic porous channels is investigated for the first time via statistical breakthrough curves. Assuming that the number of arrived molecules can be approximated as a Gaussian random variable and using fully resolved computational fluid dynamics results for the breakthrough curves, the numerical results for the throughput, mutual information, error probability, and information diversity gain are presented. Using these numerical results, the unique characteristics of the porous medium channel are revealed.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QC Physics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
| Library of Congress Subject Headings (LCSH): | Molecular communication (Telecommunication) , Cell interaction, Porous materials -- Fluid dynamics, Nanonetworks | ||||||||
| Journal or Publication Title: | IEEE Transactions on Molecular, Biological, and Multi-Scale Communications | ||||||||
| Publisher: | IEEE | ||||||||
| ISSN: | 2372-2061 | ||||||||
| Official Date: | December 2019 | ||||||||
| Dates: |
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| Volume: | 4 | ||||||||
| Number: | 4 | ||||||||
| Page Range: | pp. 257-262 | ||||||||
| DOI: | 10.1109/TMBMC.2019.2937297 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 28 August 2019 | ||||||||
| Date of first compliant Open Access: | 2 September 2019 | ||||||||
| RIOXX Funder/Project Grant: |
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