Performanceconference Juan les Pins France October3

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Stochasticgeometryandcommunication networks BartekB?aszczyszyn tutoriallecture Performanceconference Juan-les-Pins,France,October3-7,2005 INRIA-ENS OUTLINE IPanoramaofsomestochastic-geometrymodelsinaction, IIBasicgeometricmodels, IIISignal-to-Interference-and-Noiseratio(SINR)coveragemodel, IVModelingad-hocnetworks, VPowercontrolinCDMA:from statictodynamicmodeling — aspatialErlang formula. Stochasticgeometryandcommunicationnetworks, B .B?aszczyszyn; tutoriallecture ,Performance'05,Juan-les-Pins,France ,October3-7,2005 2 IPANORAMA •ThemathematicalprincipleoftheVoronoitessellationiswidelyusedasasimple idealizationofmanycomplex “real”partitionsoftheplane( cellsincellular communication ,Gupta&Kumarprotocolmodelofad-hocnetworks;ittakesinto accountonlylocationsofantennasandignoresallotherphysicalaspectsofthe communicationtechnologyasa.g.additiveinterference) •ThedualDelaunaygraphcanbeusedasa “protocolmodel”ofneighbuorhoodin networks ? topologyforrouting Stochasticgeometryandcommunicationnetworks, B .B?aszczyszyn; tutoriallecture ,Performance'05,Juan-les-Pins,France ,October3-7,2005 3 PANORAMA... •Booleanmodelisafirstmodelofcoverageofwirelessnetwork(itdoesnottake intoaccountinterference).Astheunderlyingmodelforthestudyofcontinuum percolationitcanbeusedtoaddressthequestionsofconnectivityofad-hoc networksintheabsenceofinterference . •Mathematicalrepresentationofinterferencesbasedon(Poisson)shotnoise processes? avarietyofresultsoncoverage ,connectivityandcapacityoflarge interference-limitednetworks . Stochasticgeometryandcommunicationnetworks, B .B?aszczyszyn; tutoriallecture ,Performance'05,Juan-les-Pins,France ,October3-7,2005 4

  • networks ?

  • percolationitcanbeusedtoaddressthequestionsofconnectivityofad-hoc networksintheabsenceofinterference

  • outline ipanoramaofsomestochastic-geometrymodelsinaction

  • statictodynamicmodeling —

  • ci istheregionwherethesinrfromxi

  • shot-noise

  • hocnetworks

  • edgesofthe delaunaygraphconnectnu- cleioftheadjacentcells

  • random variable


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