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Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming
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Intelligent reflecting surface (IRS) is envisioned to be a new and revolutionizing technology for achieving spectrum and energy efficient wireless communication networks cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each reflecting the incident signal with a certain phase shift to collaboratively achieve beamforming and/or interference suppression at designated receivers. In this paper, we study an IRS-aided multiuser multiple-input single-output (MISO) wireless system where one IRS is deployed to assist in the communication from a multi-antenna access point (AP) to multiple single-antenna users. As such, each user receives the superposed signals from the AP as well as the IRS via its reflection. We aim to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users' individual signal-to-interference-plus-noise ratio (SINR) constraints. However, the formulated problem is non-convex and difficult to be solved optimally.
Forward citations
Cited by 2 Pith papers
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Demystifying the Power Scaling Law of Intelligent Reflecting Surfaces and Metasurfaces
A proof that, at the same array location, Massive MIMO always achieves higher SNR than an IRS, despite the IRS's faster N^2 scaling.
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Optimizations with Intelligent Reflecting Surfaces (IRSs) in 6G Wireless Networks: Power Control, Quality of Service, Max-Min Fair Beamforming for Unicast, Broadcast, and Multicast with Multi-antenna Mobile Users and Multiple IRSs
The paper extends IRS beamforming optimization to broadcast, multicast, max-min fairness, and multi-IRS/multi-antenna settings using standard SDR alternating optimization, without numerical validation.
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