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A Survey of Intelligent Reflecting Surfaces (IRSs): Towards 6G Wireless Communication Networks

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arxiv 1907.04789 v3 pith:FDSFZTCH submitted 2019-07-08 eess.SP cs.ITcs.NImath.IT

classification eess.SPcs.ITcs.NImath.IT
keywords irssnetworkscommunicationswirelesscommunicationintelligentrecentreflecting
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Intelligent reflecting surfaces (IRSs) tune wireless environments to increase spectrum and energy efficiencies. In view of much recent attention to the IRS concept as a promising technology for 6G wireless communications, we present a survey of IRSs in this paper. Specifically, we categorize recent research studies of IRSs as follows. For IRS-aided communications, the summary includes capacity/data rate analyses, power/spectral optimizations, channel estimation, deep learning-based design, and reliability analysis. Then we review IRSs implementations as well as the use of IRSs in secure communications, terminal-positioning, and other novel applications. We further identify future research directions for IRSs, with an envision of the IRS technology playing a critical role in 6G communication networks similar to that of massive MIMO in 5G networks. As a timely summary of IRSs, our work will be of interest to both researchers and practitioners working on IRSs for 6G networks.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Performance Analysis of Fluid Antenna System under Spatially-Correlated Rician Fading Channels

    cs.IT 2025-05 reject novelty 4.0 of 10

    The paper gives outage and rate formulas for a single fluid antenna with N correlated ports under Rician fading, claims diversity order N, and says planar port layouts beat linear ones.

  2. 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

    cs.IT 2019-08 conditional novelty 4.0 of 10

    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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