A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE wireless communications letters Jg. 12; H. 2; S. 1
Hauptverfasser: Kumar, Vaibhav, Zhang, Rui, Renzo, Marco Di, Tran, Le-Nam
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
IEEE comsoc
Schlagworte:
Beamforming
Benchmark testing
Benchmarks
Communications systems
Complexity theory
Downlink
Downlinking
Engineering Sciences
Intelligent reflecting surface
Interference
Iterative methods
MISO (control systems)
MU-MISO
Optimization
Quality of service
reconfigurable intelligent surfaces
second-order cone programming
Signal and Image processing
Signal to noise ratio
successive convex approximation
second-order cone programming
reconfigurable intelligent surfaces
Intelligent reflecting surface
MU-MISO
successive convex approximation
ISSN:2162-2337, 2162-2345
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRS-assisted multiuser multiple-input single-output downlink communication system. In particular, we propose a new successive convex approximation based second-order cone programming approach in which all the optimization variables are simultaneously updated in each iteration. Our proposed scheme achieves superior performance compared to state-of-the-art benchmark solutions. In addition, the complexity of the proposed scheme is O(Ns3.5), while that of state-of-the-art benchmark schemes is O(Ns7), where Ns denotes the number of reflecting elements at the IRS.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2022.3224316