Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces

The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recent...

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Main Authors: Emil Bjornson, Luca Sanguinetti
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9184098/
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spelling doaj-cba182f546d04b0aab6dc9e52296fabc2021-03-29T18:57:13ZengIEEEIEEE Open Journal of the Communications Society2644-125X2020-01-0111306132410.1109/OJCOMS.2020.30209259184098Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting SurfacesEmil Bjornson0https://orcid.org/0000-0002-5954-434XLuca Sanguinetti1https://orcid.org/0000-0002-2577-4091Department of Electrical Engineering (ISY), Link&#x00F6;ping University, Link&#x00F6;ping, SwedenDipartimento di Ingegneria dell&#x2019;Informazione, University of Pisa, Pisa, ItalyThe use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since these can relay signals to achieve an SNR that grows as N<sup>2</sup>, which seems like a major benefit. In this article, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where N &#x2192; &#x221E;. We derive an exact channel gain expression that captures three essential near-field behaviors and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how much larger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behave as an &#x201C;anomalous&#x201D; mirror but can vastly outperform that benchmark.https://ieeexplore.ieee.org/document/9184098/Intelligent reflecting surfacereconfigurable intelligent surfacesoftware-controlled meta-surfacemassive MIMOregenerative MIMO relaysasymptotic limits
collection DOAJ
language English
format Article
sources DOAJ
author Emil Bjornson
Luca Sanguinetti
spellingShingle Emil Bjornson
Luca Sanguinetti
Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
IEEE Open Journal of the Communications Society
Intelligent reflecting surface
reconfigurable intelligent surface
software-controlled meta-surface
massive MIMO
regenerative MIMO relays
asymptotic limits
author_facet Emil Bjornson
Luca Sanguinetti
author_sort Emil Bjornson
title Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
title_short Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
title_full Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
title_fullStr Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
title_full_unstemmed Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
title_sort power scaling laws and near-field behaviors of massive mimo and intelligent reflecting surfaces
publisher IEEE
series IEEE Open Journal of the Communications Society
issn 2644-125X
publishDate 2020-01-01
description The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since these can relay signals to achieve an SNR that grows as N<sup>2</sup>, which seems like a major benefit. In this article, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where N &#x2192; &#x221E;. We derive an exact channel gain expression that captures three essential near-field behaviors and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how much larger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behave as an &#x201C;anomalous&#x201D; mirror but can vastly outperform that benchmark.
topic Intelligent reflecting surface
reconfigurable intelligent surface
software-controlled meta-surface
massive MIMO
regenerative MIMO relays
asymptotic limits
url https://ieeexplore.ieee.org/document/9184098/
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