An extension of clarke's model with stochastic amplitude flip processes

Handle URI:
http://hdl.handle.net/10754/563622
Title:
An extension of clarke's model with stochastic amplitude flip processes
Authors:
Hoel, Hakon; Nyberg, Henrik
Abstract:
Stochastic modeling is an essential tool for studying statistical properties of wireless channels. In multipath fading channel (MFC) models, the signal reception is modeled by a sum of wave path contributions, and Clarke's model is an important example of such which has been widely accepted in many wireless applications. However, since Clarke's model is temporally deterministic, Feng and Field noted that it does not model real wireless channels with time-varying randomness well. Here, we extend Clarke's model to a novel time-varying stochastic MFC model with scatterers randomly flipping on and off. Statistical properties of the MFC model are analyzed and shown to fit well with real signal measurements, and a limit Gaussian process is derived from the model when the number of active wave paths tends to infinity. A second focus of this work is a comparison study of the error and computational cost of generating signal realizations from the MFC model and from its limit Gaussian process. By rigorous analysis and numerical studies, we show that in many settings, signal realizations are generated more efficiently by Gaussian process algorithms than by the MFC model's algorithm. Numerical examples that strengthen these observations are also presented. © 2014 IEEE.
KAUST Department:
Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Communications
Issue Date:
Jul-2014
DOI:
10.1109/TCOMM.2014.2328595
Type:
Article
ISSN:
00906778
Sponsors:
This work was supported in part by the Center for Industrial and Applied Mathematics at the Royal Institute of Technology (KTH) and in part by the King Abdullah University of Science and Technology Strategic Research Initiative Center for Uncertainty Quantification in Computational Science. The associate editor coordinating the review of this paper and approving it for publication was O. Oyman.
Appears in Collections:
Articles; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHoel, Hakonen
dc.contributor.authorNyberg, Henriken
dc.date.accessioned2015-08-03T12:04:38Zen
dc.date.available2015-08-03T12:04:38Zen
dc.date.issued2014-07en
dc.identifier.issn00906778en
dc.identifier.doi10.1109/TCOMM.2014.2328595en
dc.identifier.urihttp://hdl.handle.net/10754/563622en
dc.description.abstractStochastic modeling is an essential tool for studying statistical properties of wireless channels. In multipath fading channel (MFC) models, the signal reception is modeled by a sum of wave path contributions, and Clarke's model is an important example of such which has been widely accepted in many wireless applications. However, since Clarke's model is temporally deterministic, Feng and Field noted that it does not model real wireless channels with time-varying randomness well. Here, we extend Clarke's model to a novel time-varying stochastic MFC model with scatterers randomly flipping on and off. Statistical properties of the MFC model are analyzed and shown to fit well with real signal measurements, and a limit Gaussian process is derived from the model when the number of active wave paths tends to infinity. A second focus of this work is a comparison study of the error and computational cost of generating signal realizations from the MFC model and from its limit Gaussian process. By rigorous analysis and numerical studies, we show that in many settings, signal realizations are generated more efficiently by Gaussian process algorithms than by the MFC model's algorithm. Numerical examples that strengthen these observations are also presented. © 2014 IEEE.en
dc.description.sponsorshipThis work was supported in part by the Center for Industrial and Applied Mathematics at the Royal Institute of Technology (KTH) and in part by the King Abdullah University of Science and Technology Strategic Research Initiative Center for Uncertainty Quantification in Computational Science. The associate editor coordinating the review of this paper and approving it for publication was O. Oyman.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectGaussian processesen
dc.subjectMultipath channelsen
dc.subjectray tracingen
dc.titleAn extension of clarke's model with stochastic amplitude flip processesen
dc.typeArticleen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalIEEE Transactions on Communicationsen
dc.contributor.institutionDepartment of Numerical Analysis and Computer Science, Royal Institute of Technology (KTH), 100 44 Stockholm, Swedenen
dc.contributor.institutionEricsson AB, 164 80 Stockholm, Swedenen
kaust.authorHoel, Hakonen
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