Intelligent Reflecting Surfaces for Wireless Networks: Deployment Architectures, Key Solutions, and Field Trials

Intelligent reflecting surfaces (IRSs) have emerged as a transformative technology for wireless networks by improving coverage, capacity, and energy efficiency through intelligent manipulation of wireless propagation environments. This article provides a comprehensive study on the deployment and coordination of IRSs for wireless networks. By addressing both single- and multi-reflection IRS architectures, we examine their deployment strategies across diverse scenarios, including point-to-point, point-to-multipoint, and point/multipoint-to-area setups. For the single-reflection case, we highlight the trade-offs between passive and active IRS architectures in terms of beamforming gain, coverage extension, and spatial multiplexing. For the multi-reflection case, we discuss practical strategies to optimize IRS deployment and element allocation, balancing cooperative beamforming gains and path-loss. The article further discusses practical challenges in IRS implementation, including environmental conditions, system compatibility, and hardware limitations. Numerical results and field tests validate the effectiveness of IRS-aided wireless networks and demonstrate their capacity and coverage improvements. Lastly, promising research directions, including movable IRSs, near-field deployments, and network-level optimization, are outlined to guide future investigations.

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Publication Details

Journal
IEEE Wireless Communications
Published
2025-05-19
DOI
https://doi.org/10.1109/mwc.001.250002
Citations
27
Primary Topic
Advanced Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
19.72
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article

Intelligent Reflecting Surfaces for Wireless Networks: Deployment Architectures, Key Solutions, and Field Trials

Zhenqiao Cheng, Qingqing Wu, Qiaoyan Peng, Jianwu Dou et al.
27 citations
IEEE Wireless Communications
Advanced Wireless Communication Technologies
19.72
article

Intelligent Reflecting Surfaces for Wireless Networks: Deployment Architectures, Key Solutions, and Field Trials

Zhenqiao Cheng, Qingqing Wu, Qiaoyan Peng, Jianwu Dou, Wen Chen, Li Ping, Yifei Yuan, Zhao Zhi-yong, Guangji Chen
article en
27 citations

Abstract

Intelligent reflecting surfaces (IRSs) have emerged as a transformative technology for wireless networks by improving coverage, capacity, and energy efficiency through intelligent manipulation of wireless propagation environments. This article provides a comprehensive study on the deployment and coordination of IRSs for wireless networks. By addressing both single- and multi-reflection IRS architectures, we examine their deployment strategies across diverse scenarios, including point-to-point, point-to-multipoint, and point/multipoint-to-area setups. For the single-reflection case, we highlight the trade-offs between passive and active IRS architectures in terms of beamforming gain, coverage extension, and spatial multiplexing. For the multi-reflection case, we discuss practical strategies to optimize IRS deployment and element allocation, balancing cooperative beamforming gains and path-loss. The article further discusses practical challenges in IRS implementation, including environmental conditions, system compatibility, and hardware limitations. Numerical results and field tests validate the effectiveness of IRS-aided wireless networks and demonstrate their capacity and coverage improvements. Lastly, promising research directions, including movable IRSs, near-field deployments, and network-level optimization, are outlined to guide future investigations.

IEEE Wireless CommunicationsVol. 32(6)
China Mobile (China) (CN), Shanghai Jiao Tong University (CN), University of Macau (MO), Nanjing University of Science and Technology (CN), ZTE (China) (CN), China Telecom (China) (CN), China Telecom (CN), City University of Macau (MO)
Openalex Percentile: Top 0%
Advanced Wireless Communication Technologies
19.72
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