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Reconfigurable intelligent surfaces for 6G: Engineering challenges and the road ahead

Future Information Technology Research Institute, Harbin Institute of Technology, Harbin 150001, China
State Key Laboratory of Mobile Network and Mobile Multimedia Technology, Shenzhen 518055
Wireless Research Institute, ZTE Corporation, Beijing 100029, China
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Abstract

Reconfigurable Intelligent Surfaces (RISs) have emerged as a pivotal technology for the Sixth-Generation (6G) communication system, showcasing the ability to configure wireless environment dynamically. Acknowledged as a breakthrough in enhancing network coverage, augmenting system capacity, and facilitating advanced applications such as Integrated Communication and Sensing (ISAC), RISs present a concrete approach to molding the future network evolution. The advancement of RIS technology necessitates a departure from idealistic assumptions and oversimplifications, compelling a progression towards models that more accurately reflect the physical attributes of hardware and the characteristics of propagation. In this paper, we delve into the practical constraints and limitations of current RIS design methodologies, conducting a comprehensive analysis based on the latest technological research advancements and product realizations. Our exploration is broad-ranging, encompassing the engineering challenges of single-point RISs, such as hardware impairments, intricacies of algorithm design, frequency spectrum-specific difficulties. A concentrated discourse is presented on novel near-field channel designs, the restrictions imposed by low-bit quantization, and the intricacies of amplitude-phase correlation constraints. This discussion aims to unearth the challenges, opportunities, and paradigmatic shifts induced by the practical deployment of RISs. The deployment challenges, networking dilemmas, simulation, and product evaluation is provided for RISs in large-scale networks from a broader system perspective. Furthermore, this paper highlights the critical need for accelerated efforts towards the commercialization of RISs. We explore the practical application revolution of RISs, encompassing engineering aspects and standardization processes. Our discussion aims to establish a foundational framework for introducing RISs into the market, acknowledging their significant potential as a game-changing technology in 6G communications.

References

[1]
D. B. da Costa, Q. Zhao, M. Chafii, F. Bader, and M. Debbah, 6G: Vision, applications, and challenges, in Fundamentals of 6G Communications and Networking, X. Lin, J. Zhang, Y. Liu, and J. Kim Eds. Cham, Switzerland: Springer International Publishing, 2023. pp. 15–69.
[2]

W. Jiang, B. Han, M. A. Habibi, and H. D. Schotten, The Road towards 6G: A comprehensive survey, IEEE Open J. Commun. Soc., vol. 2, pp. 334–366, 2021.

[3]

S. Dang, O. Amin, B. Shihada, and M. S. Alouini, What should 6G be, Nat. Electron., vol. 3, no. 1, pp. 20–29, 2020.

[4]
ITU-D SG2 Q3/2 Workshop on 5G Cybersecurity, Framework and overall objectives of the future development of IMT for 2030 and beyond, International Telecommunication Union (ITU) Recommendation (ITU-R) Workshop on 5G Cybersecurity, Technique Reports, 2024.
[5]

R. Liu, H. Lin, H. Lee, F. Chaves, H. Lim, and J. Sköld, Beginning of the journey toward 6G: Vision and framework, IEEE Commun. Mag., vol. 61, no. 10, pp. 8–9, 2023.

[6]

M. A. ElMossallamy, H. Zhang, L. Song, K. G. Seddik, Z. Han, and G. Y. Li, Reconfigurable intelligent surfaces for wireless communications: Principles, challenges, and opportunities, IEEE Trans. Cogn. Commun. Netw., vol. 6, no. 3, pp. 990–1002, 2020.

[7]

E. Björnson, Ö. Özdogan, and E. G. Larsson, Reconfigurable intelligent surfaces: Three myths and two critical questions, IEEE Commun. Mag., vol. 58, no. 12, pp. 90–96, 2020.

[8]

A. Valipour, M. H. Kargozarfard, M. Rakhshi, A. Yaghootian, and H. M. Sedighi, Metamaterials and their applications: An overview, Proc. Inst. Mech. Eng. Part L J. Mater. Des. Appl., vol. 236, no. 11, pp. 2171–2210, 2022.

[9]

M. Gao, Y. Yao, F. Yang, J. Ye, G. Liu, B. Wang, S. Liu, P. Wang, and Y. Lu, Two-dimensional materials for wireless power transfer, Device, vol. 1, no. 2, p. 100022, 2023.

[10]

C. M. Li, S. Zhang, H. Chen, and W. Ye, On the generalized Snell’s law for the design of elastic metasurfaces, J. Appl. Phys., vol. 133, no. 9, p. 095104, 2023.

[11]
J. Huang, C. X. Wang, Y. Sun, R. Feng, J. Huang, B. Guo, Z. Zhong, and T. J. Cui, Reconfigurable intelligent surfaces: Channel characterization and modeling, Proc. IEEE, vol. 110, no. 9, pp. 1290–1311, 2022.
[12]

W. Tang, J. Y. Dai, M. Z. Chen, K. K. Wong, X. Li, X. Zhao, S. Jin, Q. Cheng, and T. J. Cui, MIMO transmission through reconfigurable intelligent surface: System design, analysis, and implementation, IEEE J. Sel. Areas Commun., vol. 38, no. 11, pp. 2683–2699, 2020.

[13]

X. Yuan, Y. A. Zhang, Y. Shi, W. Yan, and H. Liu, Reconfigurable-intelligent-surface empowered wireless communications: Challenges and opportunities, IEEE Wirel. Commun., vol. 28, no. 2, pp. 136–143, 2021.

[14]

Y. Yuan, Q. Gu, A. Wang, D. Wu, and Y. Li, Recent progress in research and development of reconfigurable intelligent surface, ZTE Commun., vol. 20, no. 1, pp. 3–13, 2022.

[15]

T. Van Chien, H. Q. Ngo, S. Chatzinotas, M. Di Renzo, and B. Ottersten, Reconfigurable intelligent surface-assisted cell-free massive MIMO systems over spatially-correlated channels, IEEE Trans. Wirel. Commun., vol. 21, no. 7, pp. 5106–5128, 2022.

[16]

D. Kitayama, Y. Hama, K. Miyachi, and Y. Kishiyama, Research of transparent RIS technology toward 5G evolution & 6G, NTT Tech. Rev., vol. 19, no. 11, pp. 26–34, 2021.

[17]

M. Poulakis, 6G’s metamaterials solution: There’s plenty of bandwidth available if we use reconfigurable intelligent surfaces, IEEE Spectr., vol. 59, no. 11, pp. 40–45, 2022.

[18]

T. J. Cui, M. Q. Qi, X. Wan, J. Zhao, and Q. Cheng, Coding metamaterials, digital metamaterials and programmable metamaterials, Light. Sci. Appl., vol. 3, no. 10, p. e218, 2014.

[19]

X. Cheng, Y. Lin, W. Shi, J. Li, C. Pan, F. Shu, Y. Wu, and J. Wang, Joint optimization for RIS-assisted wireless communications: From physical and electromagnetic perspectives, IEEE Trans. Commun., vol. 70, no. 1, pp. 606–620, 2022.

[20]

H. L. Wang, H. F. Ma, M. Chen, S. Sun, and T. J. Cui, A reconfigurable multifunctional metasurface for full-space control of electromagnetic waves, Adv. Funct. Mater., vol. 31, no. 25, p. 2100275, 2021.

[21]

M. Jian, G. C. Alexandropoulos, E. Basar, C. Huang, R. Liu, Y. Liu, and C. Yuen, Reconfigurable intelligent surfaces for wireless communications: Overview of hardware designs, channel models, and estimation techniques, Intelligent and Converged Networks, vol. 3, no. 1, pp. 1–32, 2022.

[22]

M. Rahal, B. Denis, K. Keykhosravi, M. F. Keskin, B. Uguen, G. C. Alexandropoulos, and H. Wymeersch, Performance of RIS-aided near-field localization under beams approximation from real hardware characterization, EURASIP J. Wirel. Commun. Netw., vol. 2023, no. 1, p. 86, 2023.

[23]

Z. Peng, Z. Chen, C. Pan, G. Zhou, and H. Ren, Robust transmission design for RIS-aided communications with both transceiver hardware impairments and imperfect CSI, IEEE Wirel. Commun. Lett., vol. 11, no. 3, pp. 528–532, 2022.

[24]
C. Öztürk, M. F. Keskin, H. Wymeersch, and S. Gezici, On the impact of hardware impairments on RIS-aided localization, in Proc. IEEE Int. Conf. Communications (ICC 2022), Seoul, Republic of Korea, 2022, pp. 2846–2851.
[25]

C. X. Wang, J. Huang, H. Wang, X. Gao, X. You, and Y. Hao, 6G wireless channel measurements and models: Trends and challenges, IEEE Veh. Technol. Mag., vol. 15, no. 4, pp. 22–32, 2020.

[26]
J. Wang, W. Tang, Y. Han, S. Jin, X. Li, C. K. Wen, Q. Cheng, and T. J. Cui, Interplay between RIS and AI in wireless communications: Fundamentals, architectures, applications, and open research problems, IEEE J. Sel. Areas Commun. , vol. 39, no. 8, pp. 2271–2288, 2021.
[27]

J. Bian, C. X. Wang, X. Gao, X. You, and M. Zhang, A general 3D non-stationary wireless channel model for 5G and beyond, IEEE Trans. Wirel. Commun., vol. 20, no. 5, pp. 3211–3224, 2021.

[28]

C. Hu, L. Dai, S. Han, and X. Wang, Two-timescale channel estimation for reconfigurable intelligent surface aided wireless communications, IEEE Trans. Commun., vol. 69, no. 11, pp. 7736–7747, 2021.

[29]

L. Wei, C. Huang, G. C. Alexandropoulos, C. Yuen, Z. Zhang, and M. Debbah, Channel estimation for RIS-empowered multi-user MISO wireless communications, IEEE Trans. Commun., vol. 69, no. 6, pp. 4144–4157, 2021.

[30]
L. Wei, C. Huang, G. C. Alexandropoulos, and C. Yuen, Parallel factor decomposition channel estimation in RIS-assisted multi-user MISO communication, in Proc. IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 2020.
[31]

P. Yang, L. Yang, and S. Wang, Performance analysis for RIS-aided wireless systems with imperfect CSI, IEEE Wirel. Commun. Lett., vol. 11, no. 3, pp. 588–592, 2022.

[32]

X. Wei, L. Dai, Y. Zhao, G. Yu, and X. Duan, Codebook design and beam training for extremely large-scale RIS: Far-field or near-field, China Commun., vol. 19, no. 6, pp. 193–204, 2022.

[33]

G. C. Alexandropoulos, D. T. Phan-Huy, K. D. Katsanos, M. Crozzoli, H. Wymeersch, P. Popovski, P. Ratajczak, Y. Bénédic, M. H. Hamon, S. H. Gonzalez, et al., RIS-enabled smart wireless environments: Deployment scenarios, network architecture, bandwidth and area of influence, EURASIP J. Wirel. Commun. Netw., vol. 2023, no. 1, p. 103, 2023.

[34]

Y. Zhang, J. Zhang, M. Di Renzo, H. Xiao, and B. Ai, Reconfigurable intelligent surfaces with outdated channel state information: Centralized vs. distributed deployments, IEEE Trans. Commun., vol. 70, no. 4, pp. 2742–2756, 2022.

[35]

Y. Zhao and X. Lv, Network coexistence analysis of RIS-assisted wireless communications, IEEE Access, vol. 10, pp. 63442–63454, 2022.

[36]

J. Li, S. Zhang, Z. Li, J. Ma, and O. A. Dobre, User sensing in RIS-aided wideband mmWave system with beam-squint and beam-split, IEEE Trans. Commun., vol. 73, no. 2, pp. 1304–1319, 2025.

[37]

F. Zhu, X. Wang, C. Huang, Z. Yang, X. Chen, A. Al Hammadi, Z. Zhang, C. Yuen, and M. Debbah, Robust beamforming for RIS-aided communications: Gradient-based manifold meta learning, IEEE Trans. Wirel. Commun., vol. 23, no. 11, pp. 15945–15956, 2024.

[38]

X. Wang, F. Zhu, C. Huang, A. Alhammadi, F. Bader, Z. Zhang, C. Yuen, and M. Debbah, Robust beamforming with gradient-based liquid neural network, IEEE Wirel. Commun. Lett., vol. 13, no. 11, pp. 3020–3024, 2024.

[39]

Y. Mao, R. Zhang, and Y. Wang, AI-enabled reconfigurable intelligent surface: A new paradigm for wireless communication, IEEE Wirel. Commun., vol. 28, no. 3, pp. 112–117, 2021.

[40]

L. Zhang, S. Wu, and Y. Zhang, AI-driven beamforming techniques for 5G and beyond: A survey, IEEE Trans. Wirel. Commu., vol. 21, no. 9, pp. 7271–7285, 2022.

[41]

C. Huang, R. Mo, and C. Yuen, Reconfigurable intelligent surface assisted multiuser MISO systems exploiting deep reinforcement learning, IEEE J. Sel. Areas Commun., vol. 38, no. 8, pp. 1839–1850, 2020.

[42]

X. Gan, C. Huang, Z. Yang, C. Zhong, X. Chen, Z. Zhang, Q. Guo, C. Yuen, and M. Debbah, Bayesian learning for double-RIS aided ISAC systems with superimposed pilots and data, IEEE J. Sel. Top. Signal Process., vol. 18, no. 5, pp. 766–781, 2024.

[43]

X. Tong, Z. Zhang, J. Wang, C. Huang, and M. Debbah, Joint multi-user communication and sensing exploiting both signal and environment sparsity, IEEE J. Sel. Top. Signal Process., vol. 15, no. 6, pp. 1409–1422, 2021.

[44]

S. P. Chepuri, N. Shlezinger, F. Liu, G. C. Alexandropoulos, S. Buzzi, and Y. C. Eldar, Integrated sensing and communications with reconfigurable intelligent surfaces: From signal modeling to processing, IEEE Signal Process. Mag., vol. 40, no. 6, pp. 41–62, 2023.

[45]

Y. He, Y. Cai, H. Mao, and G. Yu, RIS-assisted communication radar coexistence: Joint beamforming design and analysis, IEEE J. Sel. Areas Commun., vol. 40, no. 7, pp. 2131–2145, 2022.

[46]

G. C. Trichopoulos, P. Theofanopoulos, B. Kashyap, A. Shekhawat, A. Modi, T. Osman, S. Kumar, A. Sengar, A. Chang, and A. Alkhateeb, Design and evaluation of reconfigurable intelligent surfaces in real-world environment, IEEE Open J. Commun. Soc., vol. 3, pp. 462–474, 2022.

[47]

W. Fan, M. Li, Z. Wang, and F. Zhang, Wireless cable testing for MIMO radios: A compact and cost-effective 5G radio performance test solution, IEEE Trans. Anntenas. Propag., vol. 71, no. 10, pp. 8239–8249, 2023.

[48]

X. Pei, H. Yin, L. Tan, L. Cao, Z. Li, K. Wang, K. Zhang, and E. Björnson, RIS-aided wireless communications: Prototyping, adaptive beamforming, and indoor/outdoor field trials, IEEE Trans. Commun., vol. 69, no. 12, pp. 8627–8640, 2021.

[49]
M. Jian, R. Liu, and Y. Chen, Standardization for reconfigurable intelligent surfaces: Progresses, challenges and the road ahead, in Proc. IEEE/CIC Int. Conf. Communications in China (ICCC Workshops), Xiamen, China, 2021, 337–342.
[50]

X. Mu, Y. Liu, L. Guo, J. Lin, and R. Schober, Simultaneously transmitting and reflecting (STAR) RIS aided wireless communications, IEEE Trans. Wirel. Commun., vol. 21, no. 5, pp. 3083–3098, 2022.

[51]

A. R. Ndjiongue, T. M. N. Ngatched, O. A. Dobre, H. Haas, and H. Shin, Double-sided beamforming in VLC systems using omni-digital reconfigurable intelligent surfaces, IEEE Commun. Mag., vol. 62, no. 2, pp. 150–155, 2024.

[52]

A. Araghi, M. Khalily, M. Safaei, A. Bagheri, V. Singh, F. Wang, and R. Tafazolli, Reconfigurable intelligent surface (RIS) in the sub-6 GHz band: Design, implementation, and real-world demonstration, IEEE Access, vol. 10, pp. 2646–2655, 2022.

[53]

S. Aboagye, T. M. N. Ngatched, A. R. Ndjiongue, O. A. Dobre, and H. Shin, Liquid crystal-based RIS for VLC transmitters: Performance analysis, challenges, and opportunities, IEEE Wirel. Commun., vol. 31, no. 4, pp. 98–105, 2024.

[54]
M. Jian, R. Liu, and Y. Zhao, Spatial multiplexing optimization for RIS-assisted wireless communication using practical models, in Proc. GLOBECOM 2022 - 2022 IEEE Global Communications Conf., Rio de Janeiro, Brazil, 2022, pp. 656–661.
[55]

H. D. Tuan, A. A. Nasir, Y. Chen, E. Dutkiewicz, and H. V. Poor, Quantized RIS-aided multi-user secure beamforming against multiple eavesdroppers, IEEE Trans. Inf. Forensics Secur., vol. 18, pp. 4695–4706, 2023.

[56]

Y. Han, X. Li, W. Tang, S. Jin, Q. Cheng, and T. J. Cui, Dual-polarized RIS-assisted mobile communications, IEEE Trans. Wirel. Commun., vol. 21, no. 1, pp. 591–606, 2022.

[57]
M. Li, Z. Zhang, and M. C. Tang, A compact, low-profile, wideband, electrically controlled, tri-polarization-reconfigurable antenna with quadruple gap-coupled patches, IEEE Trans. Anntenas. Propag., vol. 68, no. 8, pp. 6395–6400, 2020.
[58]

X. Qian and M. Di Renzo, Mutual coupling and unit cell aware optimization for reconfigurable intelligent surfaces, IEEE Wirel. Commun. Lett., vol. 10, no. 6, pp. 1183–1187, 2021.

[59]

M. T. Ivrlač and J. A. Nossek, Toward a Circuit Theory of Communication, IEEE Trans. Circ. Syst. I: Reg. Pap., vol. 57, no. 7, pp. 1663–1683, 2010.

[60]
J. Yang, Y. Chen, Y. Cui, Q. Wu, J. Dou, and Y. Wang, How practical phase-shift errors affect beamforming of reconfigurable intelligent surface? arXiv preprint arXiv: 2304.06388, 2023.
[61]

W. Tang, X. Chen, M. Z. Chen, J. Y. Dai, Y. Han, S. Jin, Q. Cheng, G. Y. Li, and T. J. Cui, On channel reciprocity in reconfigurable intelligent surface assisted wireless networks, IEEE Wirel. Commun., vol. 28, no. 6, pp. 94–101, 2021.

[62]

J. Zhang, J. Lin, P. Tang, W. Fan, Z. Yuan, X. Liu, H. Xu, Y. Lyu, L. Tian, and P. Zhang, Deterministic ray tracing: A promising approach to THz channel modeling in 6G deployment scenarios, IEEE Commun. Mag., vol. 62, no. 2, pp. 48–54, 2024.

[63]
G. Gougeon, Y. Corre, and M. Z. Aslam, Ray-based deterministic channel modelling for sub-THz band, in Proc. IEEE 30th Int. Symp. on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops), Istanbul, Türkiye, 2019, pp. 1–6.
[64]
J. Huang, C. X. Wang, Y. Liu, J. Sun, and W. Zhang, A novel 3D GBSM for mmWave MIMO channels, Sci. China Inf. Sci., vol. 61, no. 10, p. 102305, 2018.
[65]
P. Große, C. Schneider, G. Sommerkorn, and R. Thomä, A hybrid channel model based on WINNER for vehicle-to-X application, arXiv preprint arXiv: 1601.05929, 2016.
[66]

W. Liu, C. Pan, H. Ren, F. Shu, S. Jin, and J. Wang, Low-overhead beam training scheme for extremely large-scale RIS in near field, IEEE Trans. Commun., vol. 71, no. 8, pp. 4924–4940, 2023.

[67]
M. Rahal, B. Denis, K. Keykhosravi, B. Uguen, and H. Wymeersch, RIS-enabled localization continuity under near-field conditions, in Proc. IEEE 22nd Int. Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, 2021, pp. 436–440.
[68]

D. Dardari, N. Decarli, A. Guerra, and F. Guidi, LOS/NLOS near-field localization with a large reconfigurable intelligent surface, IEEE Trans. Wirel. Commun., vol. 21, no. 6, pp. 4282–4294, 2022.

[69]
Y. Zhang and A. Alkhateeb, Learning reflection beamforming codebooks for arbitrary RIS and non-stationary channels, arXiv preprint arXiv: 2109.14909, 2021.
[70]

Y. Liu, S. Zhang, F. Gao, J. Tang, and O. A. Dobre, Cascaded channel estimation for RIS assisted mmWave MIMO transmissions, IEEE Wirel. Commun. Lett., vol. 10, no. 9, pp. 2065–2069, 2021.

[71]

J. Zhang, H. Liu, Q. Wu, Y. Jin, Y. Chen, B. Ai, S. Jin, and T. J. Cui, RIS-aided next-generation high-speed train communications: Challenges, solutions, and future directions, IEEE Wirel. Commun., vol. 28, no. 6, pp. 145–151, 2021.

[72]

X. Xu, S. Zhang, F. Gao, and J. Wang, Sparse Bayesian learning based channel extrapolation for RIS assisted MIMO-OFDM, IEEE Trans. Commun., vol. 70, no. 8, pp. 5498–5513, 2022.

[73]

X. Wei, D. Shen, and L. Dai, Channel estimation for RIS assisted wireless communications: Part I: fundamentals, solutions, and future opportunities, IEEE Commun. Lett., vol. 25, no. 5, pp. 1398–1402, 2021.

[74]

H. Dai, W. Shen, L. Ding, S. Gong, and J. An, Subarray partition algorithms for RIS-aided MIMO communications, IEEE Internet Things J., vol. 9, no. 17, pp. 16196–16208, 2022.

[75]

K. Qu, K. Chen, J. Zhao, N. Zhang, Q. Hu, J. Zhao, T. Jiang, and Y. Feng, An electromechanically reconfigurable intelligent surface for enhancing sub-6G wireless communication signal, J. Inf. Intell., vol. 1, no. 3, pp. 207–216, 2023.

[76]

E. Dahlman, G. Mildh, S. Parkvall, P. Persson, G. Wikström, and H. Murai, 5G evolution and beyond, IEICE Trans. Commun., vol. E104.B, no. 9, pp. 984–991, 2021.

[77]
J. Zhu, Z. Liu, C. Song, Z. Xu, and C. Zhong, Low-rank and angular structures aided mmWave MIMO channel estimation with few-bit ADCs, in Proc. IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 2020, pp. 1–5.
[78]
K. Qian, L. Yao, X. Zhang, and T. Ng, MilliMirror: 3D printed reflecting surface for millimeter-wave coverage expansion, in Proc. 28th Annual Int. Conf. Mobile Computing and Networking, Sydney, Australia, 2022, pp. 15–28.
[79]

H. Luo, F. Gao, W. Yuan, and S. Zhang, Beam squint assisted user localization in near-field integrated sensing and communications systems, IEEE Trans. Wirel. Commun., vol. 23, no. 5, pp. 4504–4517, 2024.

[80]

L. Steinweg, C. Carta, and F. Ellinger, A hybrid true-time and phase-delayed approach for millimeter-wave beam steering, IEEE Trans. Microw. Theory Tech., vol. 70, no. 9, pp. 4318–4327, 2022.

[81]

L. Dai, J. Tan, Z. Chen, and H. V. Poor, Delay-phase precoding for wideband THz massive MIMO, IEEE Trans. Wirel. Commun., vol. 21, no. 9, pp. 7271–7286, 2022.

[82]

M. Jian, F. Gao, Z. Tian, S. Jin, and S. Ma, Angle-domain aided UL/DL channel estimation for wideband mmWave massive MIMO systems with beam squint, IEEE Trans. Wirel. Commun., vol. 18, no. 7, pp. 3515–3527, 2019.

[83]

Z. Chen, X. Ma, B. Zhang, Y. Zhang, Z. Niu, N. Kuang, W. Chen, L. Li, and S. Li, A survey on terahertz communications, China Commun., vol. 16, no. 2, pp. 1–35, 2019.

[84]

A. Pradhan, M. A. Abd-Elmagid, H. S. Dhillon, and A. F. Molisch, Robust optimization of RIS in terahertz under extreme molecular re-radiation manifestations, IEEE Trans. Wirel. Commun., vol. 23, no. 3, pp. 1783–1797, 2024.

[85]

Z. Wan, Z. Gao, F. Gao, M. Di Renzo, and M. S. Alouini, Terahertz massive MIMO with holographic reconfigurable intelligent surfaces, IEEE Trans. Commun., vol. 69, no. 7, pp. 4732–4750, 2021.

[86]

C. Huang, Z. Yang, G. C. Alexandropoulos, K. Xiong, L. Wei, C. Yuen, Z. Zhang, and M. Debbah, Multi-hop RIS-empowered terahertz communications: A DRL-based hybrid beamforming design, IEEE J. Sel. Areas Commun., vol. 39, no. 6, pp. 1663–1677, 2021.

[87]
M. Jian and R. Liu, Baseband signal processing for terahertz: Waveform design, modulation and coding, in Proc. Int. Wireless Communications and Mobile Computing (IWCMC), Harbin, China, 2021, pp. 1710–1715.
[88]

S. Aboagye, A. R. Ndjiongue, T. M. N. Ngatched, O. A. Dobre, and H. V. Poor, RIS-assisted visible light communication systems: A tutorial, IEEE Commun. Surv. Tutor., vol. 25, no. 1, pp. 251–288, 2023.

[89]

A. R. Ndjiongue, T. M. N. Ngatched, O. A. Dobre, and H. Haas, Digital RIS (DRIS): The future of digital beam management in RIS-assisted OWC systems, J. Light. Technol., vol. 40, no. 16, pp. 5597–5604, 2022.

[90]

C. Pan, H. Ren, K. Wang, J. F. Kolb, M. Elkashlan, M. Chen, M. Di Renzo, Y. Hao, J. Wang, A. L. Swindlehurst et al., Reconfigurable intelligent surfaces for 6G systems: Principles, applications, and research directions, IEEE Commun. Mag., vol. 59, no. 6, pp. 14–20, 2021.

[91]

Y. Ren, R. Zhou, X. Teng, S. Meng, M. Zhou, W. Tang, X. Li, C. Li, and S. Jin, On deployment position of RIS in wireless communication systems: Analysis and experimental results, IEEE Wirel. Commun. Lett., vol. 12, no. 10, pp. 1756–1760, 2023.

[92]
H. M. Ozaktas and M. A. Kutay, The fractional Fourier transform, in Proc. European Control Conf. (ECC), Porto, Portugal, 2001, pp. 1477–1483.
[93]

R. Tao, B. Deng, and Y. Wang, Research progress of the fractional Fourier transform in signal processing, Sci. China Ser. F, vol. 49, no. 1, pp. 1–25, 2006.

[94]

Y. Zhang, X. Wu, and C. You, Fast near-field beam training for extremely large-scale array, IEEE Wirel. Commun. Lett., vol. 11, no. 12, pp. 2625–2629, 2022.

[95]

F. Bohagen, P. Orten, and G. E. Oien, On spherical vs. plane wave modeling of line-of-sight MIMO channels, IEEE Trans. Commun., vol. 57, no. 3, pp. 841–849, 2009.

[96]

P. Wang, Y. Li, X. Yuan, L. Song, and B. Vucetic, Tens of gigabits wireless communications over E-band LoS MIMO channels with uniform linear antenna arrays, IEEE Trans. Wirel. Commun., vol. 13, no. 7, pp. 3791–3805, 2014.

[97]

S. N. Khonina, N. L. Kazanskiy, S. V. Karpeev, and M. Ali Butt, Bessel beam: Significance and applications: A progressive review, Micromachines, vol. 11, no. 11, p. 997, 2020.

[98]

I. V. A. K. Reddy, D. Bodet, A. Singh, V. Petrov, C. Liberale, and J. M. Jornet, Ultrabroadband terahertz-band communications with self-healing Bessel beams, Commun. Eng., vol. 2, no. 1, p. 70, 2023.

[99]
A. Singh, V. Petrov, H. Guerboukha, I. V. A. K. Reddy, E. W. Knightly, D. M. Mittleman, and J. M. Jornet, Wavefront engineering: Realizing efficient terahertz band communications in 6G and beyond, arXiv preprint arXiv: 2305.12636, 2023.
[100]

J. Zhi, Y. Guo, B. Hu, X. Wang, X. Yu, Z. Qiu, K. Huang, M. Yao, and B. Xu, Generation of polarization rotation function Bessel beams based on all-dielectric metasurfaces, Opti. Commun., vol. 550, p. 130014, 2024.

[101]

J. Wang, S. Gong, Q. Wu, and S. Ma, RIS-aided MIMO systems with hardware impairments: Robust beamforming design and analysis, IEEE Trans. Wirel. Commun., vol. 22, no. 10, pp. 6914–6929, 2023.

[102]

P. Xu, G. Chen, Z. Yang, and M. Di Renzo, Reconfigurable intelligent surfaces-assisted communications with discrete phase shifts: How many quantization levels are required to achieve full diversity, IEEE Wirel. Commun. Lett., vol. 10, no. 2, pp. 358–362, 2020.

[103]

M. Smith and Y. Guo, A comparison of methods for randomizing phase quantization errors in phased arrays, IEEE Trans. Anten. Propag., vol. 31, no. 6, pp. 821–828, 1983.

[104]
R. J. Mailloux, Phased Array Antenna Handbook. Norwood, MA, USA: Artech House, 2017.
[105]

B. Rana, S. S. Cho, and I. P. Hong, Review paper on hardware of reconfigurable intelligent surfaces, IEEE Access, vol. 11, pp. 29614–29634, 2023.

[106]
R. Long, Y. C. Liang, Y. Pei, and E. G. Larsson, Active reconfigurable intelligent surface-aided wireless communications, IEEE Trans. Wirel. Commun. , vol. 20, no. 8, pp. 4962–4975.
[107]

D. Dardari and D. Massari, Using MetaPrisms for performance improvement in wireless communications, IEEE Trans. Wirel. Commun., vol. 20, no. 5, pp. 3295–3307, 2021.

[108]

F. Costa and M. Borgese, Electromagnetic model of reflective intelligent surfaces, IEEE Open J. Commun. Soc., vol. 2, pp. 1577–1589, 2021.

[109]
B. Xu, T. Zhou, T. Xu, and Y. Wang, Reconfigurable intelligent surface configuration and deployment in three-dimensional scenarios, in Proc. IEEE Int. Conf. Communications Workshops (ICC Workshops), Montreal, Canada, 2021, pp. 1–6.
[110]
J. Sang, M. Zhou, J. Lan, B. Gao, W. Tang, X. Li, S. Jin, E. Basar, C. Li, Q. Cheng et al. , Multi-scenario broadband channel measurement and modeling for sub-6 GHz RIS-assisted wireless communication systems, arXiv preprint arXiv: 2305.07835, 2023.
[111]
T. S. Rappaport, Wireless Communications. 2nd Ed. Cambridge, UK: Cambridge University Press, 2024.
[112]

D. Gürgünoğlu, E. Björnson, and G. Fodor, Combating inter-operator pilot contamination in reconfigurable intelligent surfaces assisted multi-operator networks, IEEE Trans. Commun., vol. 72, no. 9, pp. 5884–5895, 2024.

[113]
W. Y. Chen, C. Y. Wang, R. H. Hwang, W. T. Chen, and S. Y. Huang, Impact of hardware impairment on the joint reconfigurable intelligent surface and robust transceiver design in MU-MIMO system, IEEE Trans. Mob. Comput., vol. 23, no. 5, pp. 3993–4008, 2024.
[114]
G. Chen, Q. Wu, W. Chen, Y. Hou, M. Jian, S. Zhang, and J. Li, Intelligent reflecting surface aided MIMO networks: Distributed or centralized architecture? arXiv preprint arXiv: 2310.01742, 2023.
[115]
M. H. Kumar, S. Sharma, K. Deka, and M. Thottappan, Centralized and distributed reconfigurable intelligent surfaces assisted NOMA, in Proc. National Conf. Communications (NCC), Mumbai, India, 2022, pp. 326–331.
[116]

Y. Cai, W. Yu, X. Nie, Q. Cheng, and T. Cui, Joint resource allocation for RIS-assisted heterogeneous networks with centralized and distributed frameworks, IEEE Trans. Circuits Syst. I Regul. Pap., vol. 71, no. 5, pp. 2132–2145, 2024.

[117]
G. Chen, Q. Wu, C. Wu, M. Jian, Y. Chen, and W. Chen, Static IRS meets distributed MIMO: A new architecture for dynamic beamforming, arXiv preprint arXiv: 2304.11639, 2023.
[118]
H. Guo, C. Madapatha, B. Makki, B. Dortschy, L. Bao, M. Åström, and T. Svensson, A comparison between network-controlled repeaters and reconfigurable intelligent surfaces, arXiv preprint arXiv: 2211.06974, 2022.
[119]
E. Basar and I. Yildirim, SimRIS channel simulator for reconfigurable intelligent surface-empowered communication systems, in Proc. IEEE Latin-American Conf. Communications (LATINCOM), Santo Domingo, Dominican Republic, 2020, pp. 1–6.
[120]

Y. Liu, J. Dou, Y. Cui, Y. Chen, J. Yang, F. Qin, and Y. Wang, Reconfigurable intelligent surface physical model in channel modeling, Electronics, vol. 11, no. 17, p. 2798, 2022.

[121]

R. Liu, J. Dou, P. Li, J. Wu, and Y. Cui, Simulation and field trial results of reconfigurable intelligent surfaces in 5G networks, IEEE Access, vol. 10, pp. 122786–122795, 2022.

[122]
M. Di Renzo, From walls at the office to sides of buildings, what if these surfaces can manage the way in which wireless signals propagate? https://www.comsoc.org/publications/ctn/walls-office-sides-buildings-what-if-these-surfaces-can-manage-way-which-wireless, 2021.
[123]

I. P. Hong, Reviews based on the reconfigurable intelligent surface technical issues, Electronics, vol. 12, no. 21, p. 4489, 2023.

[124]
R. A. Ayoubi, M. Mizmizi, D. Tagliaferri, D. De Donno, and U. Spagnolini, Network-controlled repeaters vs. reconfigurable intelligent surfaces for 6G mmW coverage extension: A simulative comparison, in Proc. 21st Mediterranean Communication and Computer Networking Conf. (MedComNet), Island of Ponza, Italy, 2023, pp. 196–202.
Intelligent and Converged Networks
Pages 53-81
Cite this article:
Zhao X, Jian M, Chen Y, et al. Reconfigurable intelligent surfaces for 6G: Engineering challenges and the road ahead. Intelligent and Converged Networks, 2025, 6(1): 53-81. https://doi.org/10.23919/ICN.2025.0004
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