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dc.contributor.authorKaradimas, Petrosen
dc.contributor.authorAllen, Benen
dc.contributor.authorSmith, Peteren
dc.date.accessioned2014-10-30T10:44:46Z
dc.date.available2014-10-30T10:44:46Z
dc.date.issued2013
dc.identifier.citationKaradimas, P., Allen, B., Smith, P. (2013) 'Human body shadowing characterization for 60-GHz indoor short-range wireless links' IEEE Antennas and Wireless Propagation Letters 12:1650en
dc.identifier.issn1536-1225
dc.identifier.issn1548-5757
dc.identifier.doi10.1109/LAWP.2013.2294563
dc.identifier.urihttp://hdl.handle.net/10547/333430
dc.description.abstractWe statistically characterize received signal power variations in the time domain caused by human activity affecting 60-GHz indoor short-range wireless links. Our approach is based on propagation measurements in indoor environments considering human activity intercepting the line-of-sight (LOS) path. It has been previously shown that the ensemble of received power levels in decibel (dB) scale cannot be modeled by a Gaussian distribution, as is the case for spatial shadowing variations. In this letter, we present a theoretical stochastic approach showing that received power variations can follow a Gaussian statistical model when considered within the time intervals of similar shadowing processes. Our model is shown to have good comparison to experimental data
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6680667en
dc.rightsArchived with thanks to IEEE Antennas and Wireless Propagation Lettersen
dc.subjectGaussian distributionen
dc.subjectindoor radioen
dc.subjecthuman body shadowing characterizationen
dc.subjectindoor short-range wireless linksen
dc.subjectwireless communication systemsen
dc.titleHuman body shadowing characterization for 60-GHz indoor short-range wireless linksen
dc.typeArticleen
dc.contributor.departmentUniversity of Bedfordshireen
dc.identifier.journalIEEE Antennas and Wireless Propagation Lettersen
html.description.abstractWe statistically characterize received signal power variations in the time domain caused by human activity affecting 60-GHz indoor short-range wireless links. Our approach is based on propagation measurements in indoor environments considering human activity intercepting the line-of-sight (LOS) path. It has been previously shown that the ensemble of received power levels in decibel (dB) scale cannot be modeled by a Gaussian distribution, as is the case for spatial shadowing variations. In this letter, we present a theoretical stochastic approach showing that received power variations can follow a Gaussian statistical model when considered within the time intervals of similar shadowing processes. Our model is shown to have good comparison to experimental data


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