D. Galappaththige, Dhanushka Kudathanthirige, Gayan Amarasuriya
{"title":"Performance Analysis of Distributed Intelligent Reflective Surface Aided Communications","authors":"D. Galappaththige, Dhanushka Kudathanthirige, Gayan Amarasuriya","doi":"10.1109/GLOBECOM42002.2020.9348102","DOIUrl":null,"url":null,"abstract":"In this paper, the performance of a distributed intelligent reflective surface (IRS)-aided communication system is investigated. To this end, the optimal signal-to-noise ratio (SNR) achievable through the direct and reflected channels is quantified by controlling the phase-shifts of the distributed IRS. This optimal SNR is statistically characterized by deriving tight approximations to the exact probability density function and cumulative distribution function for Nakagami-$m$ fading. Thereby, the outage probability and achievable rate bounds are derived in closed-form, and they are validated via Monte-Carlo simulations. Our numerical results reveal that the distributed IRS-aided communication set-ups can boost the outage and rate performance of wireless systems.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"28 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOBECOM42002.2020.9348102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
In this paper, the performance of a distributed intelligent reflective surface (IRS)-aided communication system is investigated. To this end, the optimal signal-to-noise ratio (SNR) achievable through the direct and reflected channels is quantified by controlling the phase-shifts of the distributed IRS. This optimal SNR is statistically characterized by deriving tight approximations to the exact probability density function and cumulative distribution function for Nakagami-$m$ fading. Thereby, the outage probability and achievable rate bounds are derived in closed-form, and they are validated via Monte-Carlo simulations. Our numerical results reveal that the distributed IRS-aided communication set-ups can boost the outage and rate performance of wireless systems.