Configuring Intelligent Reflecting Surface With Performance Guarantees: Optimal Beamforming

This work proposes linear time strategies to optimally configure the phase shifts for the reflective elements of an intelligent reflecting surface (IRS). Specifically, we show that the binary phase beamforming can be optimally solved in linear time to maximize the received signal-to-noise ratio (SNR...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE journal of selected topics in signal processing Jg. 16; H. 5; S. 967 - 979
Hauptverfasser: Zhang, Yaowen, Shen, Kaiming, Ren, Shuyi, Li, Xin, Chen, Xin, Luo, Zhi-Quan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Approximation
Approximation algorithms
approximation ratio
Array signal processing
Beamforming
global optimum
Intelligent reflecting surface (IRS)
linear time algorithm for discrete beamforming
Mathematical analysis
Optimization
Performance evaluation
Quadratures
Receivers
Reconfigurable intelligent surfaces
Signal processing algorithms
Signal to noise ratio
Transmitters
ISSN:1932-4553, 1941-0484
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This work proposes linear time strategies to optimally configure the phase shifts for the reflective elements of an intelligent reflecting surface (IRS). Specifically, we show that the binary phase beamforming can be optimally solved in linear time to maximize the received signal-to-noise ratio (SNR). For the general <inline-formula><tex-math notation="LaTeX">K</tex-math></inline-formula>-ary phase beamforming, we develop a linear time approximation algorithm that guarantees performance within a constant fraction <inline-formula><tex-math notation="LaTeX">(1+\cos (\pi /K))/2</tex-math></inline-formula> of the global optimum, e.g., it can attain over 85% of the optimal performance for the quadrature beamforming with <inline-formula><tex-math notation="LaTeX">K=4</tex-math></inline-formula>. According to the numerical results, the proposed approximation algorithm for discrete IRS beamforming outperforms the existing algorithms significantly in boosting the received SNR.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2022.3176479