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Demystifying the Power Scaling Law of Intelligent Reflecting Surfaces And Metasurfaces
Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..ORCID iD: 0000-0002-5954-434x
Univ Pisa, Dipartimento Ingn Informaz, I-56122 Pisa, Italy..
2019 (English)In: 2019 IEEE 8th International Workshop On Computational Advances In Multi-Sensor Adaptive Processing (CAMSAP 2019), IEEE , 2019, p. 549-553Conference paper, Published paper (Refereed)
Abstract [en]

Intelligent reflecting surfaces (IRSs) have recently attracted the attention of communication theorists as a means to control the wireless propagation channel. It has been shown that the signal-to-noise ratio (SNR) of a single-user IRS-aided transmission increases as N 2, with N being the number of passive reflecting elements in the IRS. This has been interpreted as a major potential advantage of using IRSs, instead of conventional Massive MIMO (mMIMO) whose SNR scales only linearly in N. This paper shows that this interpretation is incorrect. We first prove analytically that mMIMO always provides higher SNRs, and then show numerically that the gap is substantial; a very large number of reflecting elements is needed for an IRS to obtain SNRs comparable to mMIMO.

Place, publisher, year, edition, pages
IEEE , 2019. p. 549-553
Keywords [en]
Intelligent reflecting surface, metasurface, reflectarray, Massive MIMO, power scaling law
National Category
Signal Processing Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-296085DOI: 10.1109/CAMSAP45676.2019.9022637ISI: 000556233000107OAI: oai:DiVA.org:kth-296085DiVA, id: diva2:1664530
Conference
International Workshop On Computational Advances In Multi-Sensor Adaptive Processing (CAMSAP)
Note

QC 20220620

Available from: 2022-06-03 Created: 2022-06-03 Last updated: 2023-04-25Bibliographically approved

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Björnson, Emil

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  • fi-FI
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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