Physical-Statistical Channel Model for Off-body Area Network
In this letter, a physical-statistical-based channel model for off-body wireless communications is presented. The model utilizes a dynamic human walking model, which provides detailed description of the movement of the different body parts. The received signal is composed of a direct component, whic...
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creator | Mohamed, Marshed Kassim Cheffena, Michael Moldsvor, Arild Fontán, Fernando Pérez |
description | In this letter, a physical-statistical-based channel model for off-body wireless communications is presented. The model utilizes a dynamic human walking model, which provides detailed description of the movement of the different body parts. The received signal is composed of a direct component, which might be subject to shadowing by the body parts, and a multipath component due to reflections from the environmental scatterers. The uniform theory of diffraction (UTD) is utilized to accurately calculate the time-varying shadowing and scattering effects of the direct signal due to the moving of body parts. A Rayleigh distribution is used to represent the multipath fading effects by the scatterers around the human body. The model is validated in terms of first- and second-order statistics using 2.36 GHz measurement data, showing good agreement. |
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The model utilizes a dynamic human walking model, which provides detailed description of the movement of the different body parts. The received signal is composed of a direct component, which might be subject to shadowing by the body parts, and a multipath component due to reflections from the environmental scatterers. The uniform theory of diffraction (UTD) is utilized to accurately calculate the time-varying shadowing and scattering effects of the direct signal due to the moving of body parts. A Rayleigh distribution is used to represent the multipath fading effects by the scatterers around the human body. The model is validated in terms of first- and second-order statistics using 2.36 GHz measurement data, showing good agreement.</description><identifier>ISSN: 1516-1519</identifier><language>eng</language><publisher>IEEE</publisher><creationdate>2017</creationdate><rights>info:eu-repo/semantics/openAccess</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,777,882,26548</link.rule.ids><linktorsrc>$$Uhttp://hdl.handle.net/11250/2445550$$EView_record_in_NORA$$FView_record_in_$$GNORA$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Mohamed, Marshed Kassim</creatorcontrib><creatorcontrib>Cheffena, Michael</creatorcontrib><creatorcontrib>Moldsvor, Arild</creatorcontrib><creatorcontrib>Fontán, Fernando Pérez</creatorcontrib><title>Physical-Statistical Channel Model for Off-body Area Network</title><description>In this letter, a physical-statistical-based channel model for off-body wireless communications is presented. The model utilizes a dynamic human walking model, which provides detailed description of the movement of the different body parts. The received signal is composed of a direct component, which might be subject to shadowing by the body parts, and a multipath component due to reflections from the environmental scatterers. The uniform theory of diffraction (UTD) is utilized to accurately calculate the time-varying shadowing and scattering effects of the direct signal due to the moving of body parts. A Rayleigh distribution is used to represent the multipath fading effects by the scatterers around the human body. 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The model utilizes a dynamic human walking model, which provides detailed description of the movement of the different body parts. The received signal is composed of a direct component, which might be subject to shadowing by the body parts, and a multipath component due to reflections from the environmental scatterers. The uniform theory of diffraction (UTD) is utilized to accurately calculate the time-varying shadowing and scattering effects of the direct signal due to the moving of body parts. A Rayleigh distribution is used to represent the multipath fading effects by the scatterers around the human body. The model is validated in terms of first- and second-order statistics using 2.36 GHz measurement data, showing good agreement.</abstract><pub>IEEE</pub><oa>free_for_read</oa></addata></record> |
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title | Physical-Statistical Channel Model for Off-body Area Network |
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