2011 IEEE Vehicular Technology Conference (VTC Fall) 2011
DOI: 10.1109/vetecf.2011.6092970
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Fine Resolution Simulation of TV White Space Availability and Model Validation

Abstract: Availability of television white space is of interest for developing new data networks which operate between licensed users. The practical sensing and computational modelling of this band has been the focus of study in this and a preceding paper [1]. In this paper a high spatial resolution was used to look at the areas that a single channel was available in moderately rough terrain in the UK. The size of areas which shared available frequencies was found to be small and potential problems with spot measurement… Show more

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“…The revised code for modelling white space availability works on the same principal as previous versions [2], [4] but has been sped up and run at a much finer resolution. Additional calculation has been added to improve the estimation of power per unit bandwidth which will be shown to more accurately match field trial results and improves the availability predictions significantly.…”
Section: A Model Resultsmentioning
confidence: 99%
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“…The revised code for modelling white space availability works on the same principal as previous versions [2], [4] but has been sped up and run at a much finer resolution. Additional calculation has been added to improve the estimation of power per unit bandwidth which will be shown to more accurately match field trial results and improves the availability predictions significantly.…”
Section: A Model Resultsmentioning
confidence: 99%
“…The size of available areas of white space was found to be small though, suggesting that large scale protocols, such as 802.22 would be less well suited than the 802.11af standard. In a following paper [4] a higher resolution simulation was carried out over a small area and the size of available white space areas was confirmed to be small and scattered. In this second publication the validity of the model was also tested against a set of field trials to see how accurately the model predicted real signal strengths.…”
Section: Introductionmentioning
confidence: 91%
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