Signal-to-interference-noise-ratio density distribution for UAV-carried IRS-to-6G ground communication

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dc.contributor.authorNnamani, Christantus Obinna
dc.contributor.authorAnioke, Chidera Linda
dc.contributor.authorAl-Rubaye, Saba
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2025-04-16T10:38:48Z
dc.date.available2025-04-16T10:38:48Z
dc.date.freetoread2025-04-16
dc.date.issued2025
dc.date.pubOnline2025-03-10
dc.description.abstractThis paper investigates the probability distribution of the signal-to-interference noise ratio (SINR) for a 6G communication system comprising a multi-antenna transmitter, an intelligent reflecting surface (IRS) and a remote receiver station. A common assumption in the literature is that the density distribution function for SINR and signal-to-noise ratio (SNR) of an IRS-to-ground communication follows a Rayleigh and Rician distribution. This assumption is essential as it influences the derivation of the properties of the communication system such as the physical layer security models and the designs of IRS controller units. Therefore, in this paper, we present an analytical derivation for the density distribution functions of the SINR for an IRS-to-6G ground communication ameliorating the typical assumptions in the literature. We demonstrated that the SINR density function of an IRS-to-6G ground communication contains a hypergeometric function. We further applied the derived density distribution function to determine the average secrecy rate for passive eavesdropping.
dc.description.journalNameIEEE Access
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)
dc.description.sponsorshipThis work was supported by EPSRC Communications Hub for Empowering Distributed Cloud Computing Applications and Research (CHEDDAR) Project under Grant EP/X040518/1 and Grant EP/Y037421/1
dc.format.extentpp. 49824-49835
dc.identifier.citationNnamani, CO, Anioke CL, Al-Rubaye S, Tsourdos A. (2025) Signal-to-interference-noise-ratio density distribution for UAV-carried IRS-to-6G ground communication. IEEE Access, Volume 13, pp. 49824-49835
dc.identifier.eissn2169-3536
dc.identifier.elementsID566641
dc.identifier.issn2169-3536
dc.identifier.urihttps://doi.org/10.1109/access.2025.3549426
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23767
dc.identifier.volumeNo13
dc.language.isoen
dc.publisherIEEE
dc.publisher.urihttps://ieeexplore.ieee.org/document/10918675
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject4613 Theory Of Computation
dc.subject46 Information and Computing Sciences
dc.subject4006 Communications Engineering
dc.subject40 Engineering
dc.subject40 Engineering
dc.subject46 Information and computing sciences
dc.titleSignal-to-interference-noise-ratio density distribution for UAV-carried IRS-to-6G ground communication
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.dateAccepted2025-03-04

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