Fluid dynamics-based distance estimation algorithm for macroscale molecular communication

dc.contributor.author Güleç, Fatih
dc.contributor.author Atakan, Barış
dc.date.accessioned 2021-11-06T09:46:59Z
dc.date.available 2021-11-06T09:46:59Z
dc.date.issued 2021
dc.description.abstract Many species, from single-cell bacteria to advanced animals, use molecular communication (MC) to share information with each other via chemical signals. Although MC is mostly studied in microscale, new practical applications emerge in macroscale. It is essential to derive an estimation method for channel parameters such as distance for practical macroscale MC systems which include a sprayer emitting molecules as a transmitter (TX) and a sensor as the receiver (RX). Due to the similarity between sneezing/coughing and spraying mechanisms, these practical systems have the potential to be applied in modeling airborne pathogen (viruses, bacteria, etc.) transmission with a MC perspective where an infected human emitting pathogen-laden droplets is considered as a TX. In this paper, a novel approach based on fluid dynamics is proposed for the derivation of the distance estimation in practical MC systems. According to this approach, transmitted molecules are considered as moving and evaporating droplets in the MC channel. With this approach, the Fluid Dynamics-based Distance Estimation (FDDE) algorithm which predicts the propagation distance of the transmitted droplets by updating the diameter of evaporating droplets at each time step is proposed. FDDE algorithm is validated by experimental data. The results reveal that the distance can be estimated by the fluid dynamics approach which introduces novel parameters such as the volume fraction of droplets in a mixture of air and liquid droplets and the beamwidth of the TX. Furthermore, the effect of the evaporation is shown with the numerical results. (C) 2021 Elsevier B.V. All rights reserved. en_US
dc.description.sponsorship This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 119E041. en_US
dc.identifier.doi 10.1016/j.nancom.2021.100351
dc.identifier.issn 1878-7789
dc.identifier.issn 1878-7797
dc.identifier.scopus 2-s2.0-85101399549
dc.identifier.uri https://doi.org/10.1016/j.nancom.2021.100351
dc.identifier.uri https://hdl.handle.net/11147/11363
dc.identifier.uri https://doi.org/10.48550/arXiv.2003.11815
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation Preprint
dc.relation.hasversion Yes
dc.relation.ispartof Nano Communication Networks en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Macroscale molecular communication en_US
dc.subject Distance estimation en_US
dc.subject Airborne pathogen transmission en_US
dc.subject Practical models en_US
dc.subject Fluid dynamics en_US
dc.title Fluid dynamics-based distance estimation algorithm for macroscale molecular communication en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id 0000-0003-1031-6108
gdc.author.wosid Gulec, Fatih/AAB-1405-2020
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Electrical and Electronics Engineering en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.volume 28 en_US
gdc.description.wosquality Q2
gdc.identifier.openalex W3013448927
gdc.identifier.wos WOS:000645109200003
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.accesstype BRONZE
gdc.oaire.diamondjournal false
gdc.oaire.impulse 9.0
gdc.oaire.influence 3.0265868E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Signal Processing (eess.SP)
gdc.oaire.keywords Fluid Dynamics (physics.flu-dyn)
gdc.oaire.keywords FOS: Electrical engineering, electronic engineering, information engineering
gdc.oaire.keywords FOS: Physical sciences
gdc.oaire.keywords Physics - Fluid Dynamics
gdc.oaire.keywords Electrical Engineering and Systems Science - Signal Processing
gdc.oaire.popularity 1.0425693E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.oaire.sciencefields 0210 nano-technology
gdc.openalex.collaboration National
gdc.openalex.fwci 0.83162067
gdc.openalex.normalizedpercentile 0.66
gdc.opencitations.count 8
gdc.plumx.crossrefcites 8
gdc.plumx.mendeley 11
gdc.plumx.scopuscites 9
gdc.scopus.citedcount 9
gdc.wos.citedcount 7
relation.isAuthorOfPublication.latestForDiscovery aade0af9-6467-41ac-9cfd-a67ad66ac760
relation.isOrgUnitOfPublication.latestForDiscovery 9711dc3e-de1f-44ab-8c8a-00d8a2db8ba5

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