Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels
Large intelligent surfaces (LIS) promises not only to improve the signal to noise ratio, and spectral efficiency but also to reduce the energy consumption during the transmission. We consider a base station equipped with an antenna array using the maximum ratio transmission (MRT), and a large reflec...
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MDPI AG
2020-11-01
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author | Ricardo Coelho Ferreira Michelle S. P. Facina Felipe A. P. de Figueiredo Gustavo Fraidenraich Eduardo Rodrigues de Lima |
author_facet | Ricardo Coelho Ferreira Michelle S. P. Facina Felipe A. P. de Figueiredo Gustavo Fraidenraich Eduardo Rodrigues de Lima |
author_sort | Ricardo Coelho Ferreira |
collection | DOAJ |
description | Large intelligent surfaces (LIS) promises not only to improve the signal to noise ratio, and spectral efficiency but also to reduce the energy consumption during the transmission. We consider a base station equipped with an antenna array using the maximum ratio transmission (MRT), and a large reflector array sending signals to a single user. Each subchannel is affected by the Rayleigh flat fading, and the reflecting elements perform non-perfect phase correction which introduces a Von Mises distributed phase error. Based on the central limit theorem (CLT), we conclude that the overall channel has an equivalent Gamma fading whose parameters are derived from the moments of the channel fading between the antenna array and LIS, and also from the LIS to the single user. Assuming that the equivalent channel can be modeled as a Gamma distribution, we propose very accurate closed-form expressions for the bit error probability and a very tight upper bound. For the case where the LIS is not able to perform perfect phase cancellation, that is, under phase errors, it is possible to analyze the system performance considering the analytical approximations and the simulated results obtained using the well known Monte Carlo method. The analytical expressions for the parameters of the Gamma distribution are very difficult to be obtained due to the complexity of the nonlinear transformations of random variables with non-zero mean and correlated terms. Even with perfect phase cancellation, all the fading coefficients are complex due to the link between the user and the base station that is not neglected in this paper. |
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issn | 1424-8220 |
language | English |
last_indexed | 2024-03-10T14:39:41Z |
publishDate | 2020-11-01 |
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spelling | doaj.art-291967cc67ce42f5b033650a0a99f4582023-11-20T21:54:21ZengMDPI AGSensors1424-82202020-11-012022667910.3390/s20226679Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading ChannelsRicardo Coelho Ferreira0Michelle S. P. Facina1Felipe A. P. de Figueiredo2Gustavo Fraidenraich3Eduardo Rodrigues de Lima4DECOM/FEEC, State University of Campinas, Av. Albert Einstein 400, Campinas 13083-970, BrazilDECOM/FEEC, State University of Campinas, Av. Albert Einstein 400, Campinas 13083-970, BrazilInstituto Nacional de Telecomunicações, Santa Rita do Sapucaí 37540-000, BrazilDECOM/FEEC, State University of Campinas, Av. Albert Einstein 400, Campinas 13083-970, BrazilDepartment of Hardware Design, Instituto de Pesquisas Eldorado, Campinas 3083-898, BrazilLarge intelligent surfaces (LIS) promises not only to improve the signal to noise ratio, and spectral efficiency but also to reduce the energy consumption during the transmission. We consider a base station equipped with an antenna array using the maximum ratio transmission (MRT), and a large reflector array sending signals to a single user. Each subchannel is affected by the Rayleigh flat fading, and the reflecting elements perform non-perfect phase correction which introduces a Von Mises distributed phase error. Based on the central limit theorem (CLT), we conclude that the overall channel has an equivalent Gamma fading whose parameters are derived from the moments of the channel fading between the antenna array and LIS, and also from the LIS to the single user. Assuming that the equivalent channel can be modeled as a Gamma distribution, we propose very accurate closed-form expressions for the bit error probability and a very tight upper bound. For the case where the LIS is not able to perform perfect phase cancellation, that is, under phase errors, it is possible to analyze the system performance considering the analytical approximations and the simulated results obtained using the well known Monte Carlo method. The analytical expressions for the parameters of the Gamma distribution are very difficult to be obtained due to the complexity of the nonlinear transformations of random variables with non-zero mean and correlated terms. Even with perfect phase cancellation, all the fading coefficients are complex due to the link between the user and the base station that is not neglected in this paper.https://www.mdpi.com/1424-8220/20/22/6679large intelligent surfacesmassive MIMO systemsmaximum ratio transmissionVon Mises distributionRayleigh fading |
spellingShingle | Ricardo Coelho Ferreira Michelle S. P. Facina Felipe A. P. de Figueiredo Gustavo Fraidenraich Eduardo Rodrigues de Lima Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels Sensors large intelligent surfaces massive MIMO systems maximum ratio transmission Von Mises distribution Rayleigh fading |
title | Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels |
title_full | Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels |
title_fullStr | Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels |
title_full_unstemmed | Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels |
title_short | Large Intelligent Surfaces Communicating Through Massive MIMO Rayleigh Fading Channels |
title_sort | large intelligent surfaces communicating through massive mimo rayleigh fading channels |
topic | large intelligent surfaces massive MIMO systems maximum ratio transmission Von Mises distribution Rayleigh fading |
url | https://www.mdpi.com/1424-8220/20/22/6679 |
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