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...

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Bibliographic Details
Published in:IEEE wireless communications letters Vol. 12; no. 2; p. 1
Main Authors: Kumar, Vaibhav, Zhang, Rui, Renzo, Marco Di, Tran, Le-Nam
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
IEEE comsoc
Subjects:
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 Access:Get full text
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Summary: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.
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ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2022.3224316