The DOI matches its Crossref record; 192 of the 193 references it cites were found in a registry or an index.
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey
Open accessAbstract
This paper presents a literature review on recent applications and design aspects of the intelligent reflecting surface (IRS) in the future wireless networks. Conventionally, the network optimization has been limited to transmission control at two endpoints, i.e., end users and network controller. The fading wireless channel is uncontrollable and becomes one of the main limiting factors for performance improvement. The IRS is composed of a large array of scattering elements, which can be individually configured to generate additional phase shifts to the signal reflections. Hence, it can actively control the signal propagation properties in favor of signal reception, and thus realize the notion of a smart radio environment. As such, the IRS's phase control, combined with the conventional transmission control, can potentially bring performance gain compared to wireless networks without IRS. In this survey, we first introduce basic concepts of the IRS and the realizations of its reconfigurability. Then, we focus on applications of the IRS in wireless communications. We overview different performance metrics and analytical approaches to characterize the performance improvement of IRS-assisted wireless networks. To exploit the performance gain, we discuss the joint optimization of the IRS's phase control and the transceivers' transmission control in different network design problems, e.g., rate maximization and power minimization problems. Furthermore, we extend the discussion of IRS-assisted wireless networks to some emerging use cases. Finally, we highlight important practical challenges and future research directions for realizing IRS-assisted wireless networks in beyond 5G communications.
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“By adequately training and configuring the transmission coefficients of the meta-atoms using error backpropagation, a SIM is capable of performing desired functions through the interactions of spatial EM waves with the metasurface layers [15], [16].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [16]
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“In HOENN, the power-efficient SIM can preprocess spatial EM waves, reducing the scale requirements and the computation load for the electronic neuron network [16].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [16]
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Cites
Light Propagation with Phase Discontinuities: Generalized Laws of Reflection and Refraction
Yu, N., Genevet, P., Kats, M. A., Aieta, F., Tetienne, J.-P., Capasso, F., & Gaburro, Z. (2011) · Science · doi:10.1126/science.1210713 · Cited by 10,361
Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming
Wu, Q., & Zhang, R. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2936025 · Cited by 4,545
Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network
Wu, Q., & Zhang, R. (2019) · IEEE Communications Magazine · doi:10.1109/mcom.001.1900107 · Cited by 4,296
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
Huang, C., Zappone, A., Alexandropoulos, G. C., Debbah, M. A., & Yuen, C. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2922609 · Cited by 3,774
Wireless Communications Through Reconfigurable Intelligent Surfaces
Basar, E., Di Renzo, M., De Rosny, J., Debbah, M., Alouini, M.-S., & Zhang, R. (2019) · IEEE Access · doi:10.1109/access.2019.2935192 · Cited by 3,394
A review of metasurfaces: physics and applications
Chen, H., Taylor, A. J., & Yu, N. (2016) · Reports on Progress in Physics · doi:10.1088/0034-4885/79/7/076401 · Cited by 2,618
Holloway, C. L., Kuester, E. F., Gordon, J. A., O’Hara, J. F., Booth, J. C., & Smith, D. R. (2012) · IEEE Antennas and Propagation Magazine · doi:10.1109/map.2012.6230714 · Cited by 2,369
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Luong, N. C., Hoang, D. T., Gong, S., Niyato, D. T., Wang, P., Liang, Y., & Kim, D. I. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2916583 · Cited by 2,181
Self-citationDeep Learning in Mobile and Wireless Networking: A Survey
Zhang, C., Patras, P., & Haddadi, H. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2904897 · Cited by 1,913
Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come
Renzo, M. D., Debbah, M., Phan-Huy, D.-T., Zappone, A., Alouini, M.-S., Yuen, C., Sciancalepore, V., Alexandropoulos, G. C., Hoydis, J., Gacanin, H., et al. (2019) · EURASIP Journal on Wireless Communications and Networking · doi:10.1186/s13638-019-1438-9 · Cited by 1,717
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1 of the 193 references couldn’t be matched to a known paper.
Research works printed but not linked: 10
- lu, 2020, Intelligent Reflecting Surface (IRS)-Enabled Covert Communications in Wireless Networks
- 10.1109/GLOBECOM38437.2019.9013626 · DOI
- wu, 2019, Joint active and passive beamforming optimization for intelligent reflecting surface assisted SWIPT under QOS constraints
- zhang, 2020, Large Intelligent Surface/Antennas (LISA) Assisted Symbiotic Radio for IoT Communications
- li, 2020, Joint beamforming design in multi-cluster MISO NOMA intelligent reflecting surface-aided downlink communication networks
- 2020, A Hardware Platform for Software-Driven Functional Metasurfaces
- tang, 2019, Wireless communications with reconfigurable intelligent surface Path loss modeling and experimental measurement
- abeywickrama, 2019, Intelligent reflecting surface Practical phase shift model and beamforming optimization
- huang, 2019, Holographic MIMO surfaces for 6G wireless networks Opportunities chanllenges and trends
- wang, 2019, Intelligent reflecting surface-assisted millimeter wave communications Joint active and passive precoding design
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Robust beamforming design for RIS-assisted SWIPT systems over NOMA networks
Cao, F., Zhang, Q., Han, Z., & Wang, E. (2026) · Engineering Research Express · doi:10.1088/2631-8695/ae68d6
Metadata
- Authors
- Gong, S., Lu, X., Hoang, D. T., Niyato, D., Shu, L., Kim, D. I., & Liang, Y.-C.
- Affiliations
- Sun Yat-sen University (CN)
- University of Alberta (CA)
- University of Technology Sydney (AU)
- Nanyang Technological University (SG)
- Nanjing Agricultural University (CN)
- Sungkyunkwan University (KR)
- University of Electronic Science and Technology of China (CN)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2020
- Volume
- 22
- Issue
- 4
- Pages
- 2283-2314
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W3027118737
- Cited by
- 1,035
- References
- 193
- Citations by year
- 2026: 77 · 2025: 164 · 2024: 167 · 2023: 194 · 2022: 212 · 2021: 184 · 2020: 36
- FWCI
- 53.77
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (61972434, U1801261)
- Shenzhen Basic Research Program (JCYJ20190807154009444)
- Shenzhen Talent Peacock Plan Program (KQTD2015071715073798)
- PCL Future Greater-Bay Area Network Facilities for Largescale Experiments and Applications (LZC0019)
- National Research Foundation (NRF), Singapore, through Singapore Energy Market Authority (EMA), Energy Resilience, Singapore (NRF2017EWT-EP003-041, NRF2015-NRF-ISF001-2277)
- Singapore NRF National Satellite of Excellence, Design Science and Technology for Secure Critical Infrastructure (NSoE DeSTSCI2019-0007)
- A*STAR-NTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing (RGANS1906)
- Wallenberg AI, Autonomous Systems and Software Program and Nanyang Technological University (M4082187 (4080))
- National Research Foundation of Korea (NRF) Grant
- Korean Government (2014R1A5A1011478)
- Key Areas of Research and Development Program of Guangdong Province, China (2018B010114001)
- Central Universities Funding (ZYGX2019Z022)
- Higher Education Discipline Innovation Project (B20064)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Antenna and Metasurface Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Keywords
- reconfigurable intelligent surface, smart radio environments, phase shift control, rate maximization, power minimization, beyond 5G, wireless network design
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