Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/8822
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGüleç, Fatih-
dc.contributor.authorAtakan, Barış-
dc.date.accessioned2020-07-18T08:31:27Z-
dc.date.available2020-07-18T08:31:27Z-
dc.date.issued2020-
dc.identifier.issn1878-7789-
dc.identifier.urihttps://doi.org/10.1016/j.nancom.2020.100300-
dc.identifier.urihttps://hdl.handle.net/11147/8822-
dc.description.abstractAccurate estimation of the distance between the transmitter (TX) and the receiver (RX) in molecular communication (MC) systems can provide faster and more reliable communication. In addition, distance information can be used in determining the location of the molecular source in practical applications such as monitoring environmental pollution. Existing theoretical models in the literature are not suitable for distance estimation in a practical scenario. Furthermore, deriving an analytical model is a nontrivial problem, since the liquid in the TX is sprayed as droplets rather than molecules, these droplets move according to Newtonian mechanics, the size of the droplets change during their propagation and droplet-air interaction causes unsteady flows. Therefore, five different practical methods comprising three novel data analysis based methods and two supervised machine learning (ML) methods, Multivariate Linear Regression (MLR) and Neural Network Regression (NNR), are proposed for distance estimation at the RX side. In order to apply the ML methods, a macroscale practical MC system, which consists of an electric sprayer without a fan, alcohol molecules, an alcohol sensor and a microcontroller, is established, and the received signals are recorded. A feature extraction algorithm is proposed to utilize the measured signals as the inputs in ML methods. The numerical results show that the ML methods outperform the data analysis based methods in the root mean square error sense with the cost of complexity. The nearly equal performance of MLR and NNR shows that the input features such as peak time, peak concentration and the energy of the received signal have a highly linear relation with the distance. Moreover, the peak time based estimation, which is one of the proposed data analysis based methods, yields better results with respect to the other proposed four methods, as the distance increases. Given the experimental data and fluid dynamics theory, a possible trajectory of the molecules between the TX and RX is given. Our findings show that distance estimation performance is jointly affected by unsteady flows and the non-linearity of the sensor. According to our findings based on fluid dynamics, it is evaluated that fluid dynamics should be taken into account for more accurate parameter estimation in practical macroscale MC systems. (C) 2020 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofNano Communication Networksen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMolecular communicationen_US
dc.subjectDistance estimationen_US
dc.subjectMolecular signal processingen_US
dc.titleDistance estimation methods for a practical macroscale molecular communication systemen_US
dc.typeArticleen_US
dc.institutionauthorGüleç, Fatih-
dc.institutionauthorAtakan, Barış-
dc.departmentİzmir Institute of Technology. Electrical and Electronics Engineeringen_US
dc.identifier.volume24en_US
dc.identifier.wosWOS:000537262900005en_US
dc.identifier.scopus2-s2.0-85083312889en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.nancom.2020.100300-
dc.relation.doi10.1016/j.nancom.2020.100300en_US
dc.coverage.doi10.1016/j.nancom.2020.100300en_US
dc.identifier.wosqualityQ2-
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextopen-
crisitem.author.dept01.01. Units Affiliated to the Rectorate-
crisitem.author.dept03.05. Department of Electrical and Electronics Engineering-
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File SizeFormat 
1-s2.0-S1878778919301115-main.pdf1.39 MBAdobe PDFView/Open
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

16
checked on Mar 22, 2024

WEB OF SCIENCETM
Citations

13
checked on Mar 16, 2024

Page view(s)

648
checked on Mar 25, 2024

Download(s)

70
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.