References & Further Reading

References

G. Caire and collaborators (CommIT group, TU Berlin), Power- and Hardware-Efficient Multiuser Multibeam Array-Fed RIS Architectures for Mobile Access at mmWave, 2022
The CommIT contribution that underlies this chapter. Proposes the array-fed RIS architecture in which a small active array feeds a large passive metasurface, avoiding the double-fading loss of stand-alone RIS while keeping the RF-chain count proportional to the number of users rather than the aperture. Develops the eigenmode analysis (Section 21.3), the alternating-optimization multiuser design (Section 21.4), and the rate-versus-power comparison with fully digital arrays (Section 21.5).
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, 2020
The canonical survey on RIS and smart radio environments. Sections II and III provide the physical model and signal model used in Section 21.1. The paper's taxonomy of RIS deployments is the backdrop against which the array-fed architecture is best understood as a BS-side (rather than environment-side) use case.
E. Basar, M. Di Renzo, J. de Rosny, M. Debbah, M.-S. Alouini, and R. Zhang, Wireless Communications Through Reconfigurable Intelligent Surfaces, 2019
Influential early overview establishing the system-level framing of RIS. The historical note of Section 21.1 traces the 2019 emergence of "intelligent surfaces" as a research topic to this paper and Di Renzo et al. 2020.
Q. Wu and R. Zhang, Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming, 2019
The foundational joint-beamforming paper for RIS-aided systems. Formulates the bilinear optimization over $\ntn{prec}$ and $\boldsymbol{\phi}$ that Section 21.4 specializes to the array- fed case, and introduces the SDR-based relaxation that inspires the alternating-optimization algorithm of this chapter.
E. Bjornson, O. Ozdogan, and E. G. Larsson, Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?, 2020
A clear-eyed comparison of passive RIS to DF relays, showing that a 1 W relay with 100 receive antennas typically beats a 1000-element passive RIS. The paper is the empirical backbone of the double-fading analysis in Section 21.1 and motivates the array-fed architecture in Section 21.2 as a way to overcome the RIS's inherent disadvantage.
Y. Yu, D. Wang, and J. Zhang, Active Array Feed Architectures for Beamforming via Metasurface Reflectors, 2020
An antenna-theoretic derivation of the array-fed metasurface link budget, arriving at an expression consistent with Theorem <a href="#thm-af-ris-link-budget" class="ferkans-ref" title="Theorem: Array-Fed RIS Link Budget (Single User, LOS)" data-ref-type="theorem"><span class="ferkans-ref-badge">T</span>Array-Fed RIS Link Budget (Single User, LOS)</a>. Complements the communication- theoretic treatment of this chapter with physical-layer details on the near-field coupler $\mathbf{G}_f$.
P. Nayeri, F. Yang, and A. Z. Elsherbeni, Reflectarray Antennas: Theory, Designs, and Applications, 2018
The definitive reference on passive reflectarrays, the technological ancestor of RIS. Chapter 2 covers the array manifold and coupling analysis used in the eigenmode derivation of Section 21.3. Reading this book after this chapter helps bridge the communication and antenna-engineering perspectives.
R. W. Heath Jr., N. Gonzalez-Prelcic, S. Rangan, W. Roh, and A. M. Sayeed, An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems, 2016
The reference mmWave survey. Section IV on hybrid beamforming provides the conceptual framework that Section 21.2 extends to replace phase-shifter networks with a metasurface analog stage. The Caire 2022 array-fed RIS is best understood as "hybrid beamforming with a metasurface analog stage."
E. Bjornson, L. Sanguinetti, J. Hoydis, and M. Debbah, Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?, 2018
The definitive energy-efficiency analysis of multi-user MIMO. Section III of this paper defines the DC power model ($P_c^{\text{RF}}$, $P_{\text{BB}}$, $P_0$) used in Section 21.5 to compare array-fed RIS with fully digital arrays.
Z. Wang, L. Liu, and S. Cui, Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis, 2020
Principal reference for the cascaded-channel estimation problem discussed briefly in the Section 21.4 remark. Shows that pilot overhead scales as $\mathcal{O}(N_{\text{RIS}}/N_a)$ in the uncompressed regime and $\mathcal{O}(s\log(N_{\text{RIS}}/s))$ under $s$-sparse angular structure.
C. Huang, G. C. Alexandropoulos, A. Zappone, M. Debbah, and C. Yuen, Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces, 2019
Early paper exploring ML-based RIS phase design. While our chapter uses classical alt-opt, the ML perspective is growing — interested readers should follow up with Alexandropoulos's subsequent work (not cited here) on GNN-based RIS control.
W. Tang, M. Z. Chen, X. Chen, J. Y. Dai, Y. Han, M. Di Renzo, Y. Zeng, S. Jin, Q. Cheng, and T. J. Cui, Wireless Communications with Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement, 2021
The experimental validation of the double-fading law with hardware RIS prototypes. Reports measured $N_{\text{RIS}}^2$ scaling of the reflected SNR at 10.5 GHz and 27 GHz, confirming the theoretical model behind Theorem <a href="#thm-double-fading" class="ferkans-ref" title="Theorem: Double-Fading Path Loss" data-ref-type="theorem"><span class="ferkans-ref-badge">T</span>Double-Fading Path Loss</a>.