References

References

  1. Q. Wu and R. Zhang, Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming, IEEE Transactions on Wireless Communications, 2019

    The foundational paper on joint active-passive beamforming for RIS-assisted communication. Introduces the alternating optimisation framework and SDR-based phase optimisation with unit-modulus constraints. Shows that the SDR achieves an approximation ratio of $\pi/4$ for the single-user case. The primary reference for Section 28.3.

  2. E. Bj\"{o}rnson, \"{O}. \"{O}zdogan, and E. G. Larsson, Intelligent Reflecting Surface versus Decode-and-Forward: How Large a Surface Is Needed to Beat Relaying?, IEEE Wireless Communications Letters, 2020

    A critical comparison between RIS and decode-and-forward relaying. Derives the crossover point at which the $N^2$ scaling of RIS overcomes the single-hop advantage of relays, accounting for realistic path loss models. Shows that hundreds to thousands of RIS elements may be needed to match a modest relay. The primary reference for the crossover analysis in Section 28.4.

  3. M. Di Renzo, A. Zappone, M. Debbah, M.-S. Alouini, C. Yuen, J. de Rosny, and S. Tretyakov, Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and the Road Ahead, IEEE Journal on Selected Areas in Communications, 2020

    A comprehensive tutorial and survey on RIS technology covering electromagnetic foundations, communication-theoretic analysis, channel modelling, and open research challenges. Bridges the gap between the physics of metasurfaces and the signal processing perspective. A key reference for the physical realisation discussion in Section 28.1 and the open problems in Section 28.5.

  4. C. Huang, A. Zappone, G. C. Alexandropoulos, M. Debbah, and C. Yuen, Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication, IEEE Transactions on Wireless Communications, 2019

    One of the earliest works on RIS-aided energy-efficient communication. Formulates the energy efficiency maximisation problem with joint active-passive beamforming and proposes alternating optimisation and sequential fractional programming solutions. Demonstrates that RIS can significantly improve energy efficiency compared to conventional relay-based systems.

  5. Q. Wu and R. Zhang, Beamforming Optimization for Wireless Networks Aided by Intelligent Reflecting Surface With Discrete Phase Shifts, IEEE Transactions on Communications, 2020

    Extends the joint beamforming framework to discrete (quantised) phase shifts. Derives the performance loss due to finite-bit phase control and shows that 2--3 bits per element are sufficient to approach the continuous-phase performance. The primary reference for the phase quantisation analysis in Section 28.5.

  6. D. Mishra and H. Johansson, Channel Estimation and Low-Complexity Beamforming Design for Passive Intelligent Surface Assisted MISO Wireless Energy Transfer, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019

    Introduces the ON/OFF channel estimation protocol for passive RIS elements, where individual elements are activated sequentially to estimate the cascaded channel. A foundational reference for the channel estimation discussion in Section 28.2.

  7. G. Caire, G. D. Gonzalez, and R. Salihu, Multiuser Multibeam Array-Fed RIS Architecture for Sub-THz Communications, IEEE Transactions on Wireless Communications, 2023

    Proposes an array-fed RIS architecture where a small active antenna array feeds a large passive RIS, creating multiple independent beams for multiuser communication at sub-THz frequencies. Shows that the array-fed RIS can achieve near-optimal multiuser rates with much lower hardware cost than a fully digital massive MIMO array at the same aperture size. A key CommIT group contribution to RIS research.

  8. B. Zheng, C. You, W. Mei, and R. Zhang, A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications, IEEE Communications Surveys and Tutorials, 2022

    A comprehensive survey covering channel estimation protocols (ON/OFF, DFT-based, compressed sensing, two-timescale), practical beamforming algorithms, and the interaction between estimation accuracy and beamforming performance for RIS systems. The primary survey reference for Section 28.2.

Further Reading

For readers who want to go deeper into specific topics from this chapter.

  • Electromagnetic foundations and physics of RIS

    S. Tretyakov, "Analytical Modeling in Applied Electromagnetics," Artech House, 2003; and M. Di Renzo et al., "Communication Models for Reconfigurable Intelligent Surfaces: From Surface Electromagnetics to Wireless Networks Optimization," Proc. IEEE, 2022

    The communication-theoretic models used in this chapter abstract away the electromagnetic physics. These references provide the physical foundations: how metasurface elements manipulate electromagnetic waves, the relationship between element impedance and reflection coefficient, and how to bridge physics-based and communication-based models.

  • Near-field RIS and extremely large aperture arrays (ELAA)

    H. Lu and Y. Zeng, "Communicating with Extremely Large-Scale Array/Surface: Unified Modelling and Performance Analysis," IEEE Trans. Wireless Commun., 2024

    When the RIS has thousands of elements, users may fall within the near-field (Fresnel) region where the plane-wave assumption breaks down. This reference develops near-field channel models and analyses how the $N^2$ scaling law is modified when the wavefront curvature cannot be neglected.

  • RIS-aided integrated sensing and communication (ISAC)

    X. Song, J. Xu, F. Liu, T. X. Han, and Y. C. Eldar, "Intelligent Reflecting Surface Enabled Sensing: Fundamentals and Opportunities," IEEE Communications Magazine, 2023

    RIS can create controllable multipath to assist radar sensing and user localisation simultaneously with communication. This reference covers the joint beamforming design for dual-function RIS systems and the fundamental performance trade-offs between communication rate and sensing accuracy.

  • Multi-RIS and RIS network deployment

    W. Mei and R. Zhang, "Cooperative Beam Routing for Multi-IRS Aided Communication," IEEE Wireless Commun. Letters, 2021; and Z. Abdullah et al., "Intelligent Reflecting Surface-Assisted Multi-UAV MIMO Communications," IEEE JSAC, 2022

    Practical deployments may feature multiple RIS panels that must be jointly optimised. These references address cooperative multi-RIS beam routing (where a signal bounces off multiple surfaces) and network-level RIS deployment optimisation with mobile access points.

ExercisesCh 29 →