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dc.contributor.authorRamirez, Juan Marcos 
dc.contributor.authorMancuso, Vincenzo 
dc.contributor.authorAjmone Marsan, Marco 
dc.date.accessioned2024-07-15T13:17:53Z
dc.date.available2024-07-15T13:17:53Z
dc.date.issued2024-07-31
dc.identifier.urihttps://hdl.handle.net/20.500.12761/1827
dc.description.abstractReconfigurable intelligent surfaces (RISs) have emerged as a key technology for future communication systems. RISs are arrays of tunable reflecting elements that provide controllable propagation channels by smartly shaping incident electromagnetic (EM) waves. Analysis and improvement of RIS-aided systems require the definition of accurate path loss models that consider environmental effects often encountered in practical applications. In this paper, we derive a path loss model for RIS-assisted communications to account for the attenuation induced by the transmission medium and randomly located obstructions. More precisely, this study focuses on assessing the impact caused by Poisson-located obstructing objects on RIS-assisted millimeter wave links. To this end, we evaluate the outage probability yielded by RIS-aided systems in indoor environments with antenna beam-steering and random obstructions. We obtain extensive simulation results to assess the impact of RIS considering different parameters, such as the minimum signal-to-noise ratio (SNR) necessary for successful reception, the operating frequency, the density of the Poisson process used for object placement, and the object size.es
dc.description.sponsorshipMinistry of Economic Affairs and Digital Transformation, European Union NextGeneration-EUes
dc.language.isoenges
dc.titleThe Rumble in the Millimeter Wave Jungle: Obstructions Vs RISes
dc.typeconference objectes
dc.conference.date10-13 June 2024es
dc.conference.placeNice, Francees
dc.conference.titleMediterranean Communication and Computer Networking Conference*
dc.event.typeconferencees
dc.pres.typepaperes
dc.type.hasVersionAOes
dc.rights.accessRightsembargoed accesses
dc.page.final10es
dc.page.initial1es
dc.relation.projectIDTSI-063000-2021-38es
dc.relation.projectNameAEON-CPS Network Intelligence for cyber-physical system supportes
dc.subject.keywordmmWave links, path loss modeling, outage probability, reconfigurable intelligent surfaces.es
dc.description.awardsMario Gerla Best Paper Awardes
dc.description.refereedTRUEes
dc.description.statusinpresses


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