References & Further Reading

References

1. D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, 2005. [Link]

   Chapter 7 covers MIMO capacity and fading statistics. Section 2.4 derives the Rayleigh fading distribution. The standard graduate reference for wireless channel fundamentals.

2. E. Björnson, J. Hoydis, and L. Sanguinetti, Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency, 2017

   The definitive massive MIMO textbook for this chapter. Chapter 2 covers channel models exhaustively, including one-ring, Kronecker, and the role of spatial correlation in channel hardening and favorable propagation.

3. A. M. Sayeed, Deconstructing Multiantenna Fading Channels, 2002

   The original paper introducing the virtual channel representation. Theorem 1 establishes the sparsity result. Section III derives the DFT-domain characterization. Essential reading for Section 3 of this chapter.

4. A. Adhikary, J. Nam, J.-Y. Ahn, and G. Caire, Joint Spatial Division and Multiplexing — The Large-Scale Array Regime, 2013

   The JSDM paper that uses the one-ring model as its foundation. Sections I–II give a clear exposition of the one-ring model and angular separation conditions. Chapter 7 of this book covers JSDM in full.

5. W. Weichselberger, M. Herdin, H. Özcelik, and E. Bonek, A Stochastic MIMO Channel Model with Joint Correlation of Both Link Ends, 2006

   Introduces the Weichselberger model and demonstrates through indoor measurements at 5.2 GHz that it captures joint TX-RX coupling better than the Kronecker model. Sections II–IV develop the model; Section V provides measurement validation.

6. J. P. Kermoal, L. Schumacher, K. I. Pedersen, P. E. Mogensen, and F. Frederiksen, A Stochastic MIMO Radio Channel Model with Experimental Validation, 2002

   The original Kronecker model paper, validated against indoor measurements. Introduces the $\mathbf{R}_t \otimes \mathbf{R}_r$ covariance factorization and provides the theoretical framework for spatial correlation analysis.

7. 3GPP, Study on Channel Model for Frequencies from 0.5 to 100 GHz, 2023. [Link]

   The definitive 3GPP channel model specification. Tables 7.5-6 through 7.5-11 give large-scale parameter statistics for UMa, UMi, RMa, and InH scenarios. Section 7.7 specifies the CDL and TDL simplified models.

8. S. Jaeckel, L. Raschkowski, K. Borner, and L. Thiele, QuaDRiGa: A 3-D Multi-Cell Channel Model with Time Evolution for Enabling Virtual Field Trials, 2014

   The QuaDRiGa channel simulator paper. Section II describes the spatial consistency model. The software is freely available and implements TR 38.901 with additional features including dual mobility and multi-frequency correlation.

9. R. Couillet and M. Debbah, Random Matrix Methods for Wireless Communications, Cambridge University Press, 2011

   The rigorous treatment of the Marchenko–Pastur law and related results for MIMO capacity analysis. Chapter 1 covers the Stieltjes transform method. Chapter 3 applies random matrix theory to MIMO channel capacity. Prerequisite: graduate probability theory.

10. T. S. Rappaport, S. Sun, R. Mayzus, H. Zhao, Y. Azar, K. Wang, G. N. Wong, J. K. Schulz, M. Samimi, and F. Gutierrez, Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!, 2013

    Seminal NYU Wireless paper presenting early 28 GHz and 38 GHz measurement results. Sections IV–V report cluster statistics confirming sparse scattering at mmWave. A key reference for Section 5 of this chapter.

11. A. F. Molisch, Wireless Communications, Wiley-IEEE Press, 2nd ed., 2011

    Comprehensive wireless textbook. Chapter 6 covers channel sounding methodology. Chapter 7 details MIMO channel models including the one-ring and Kronecker models. Part IV covers propagation measurement techniques.

12. A. F. Molisch, V. V. Ratnam, S. Han, Z. Li, S. L. H. Nguyen, L. Li, and K. Haneda, Hybrid Beamforming for Massive MIMO: A Survey, 2017

    Survey covering hybrid beamforming architectures and their connection to mmWave channel sparsity. Section 4 discusses the hardware constraints that motivate hybrid architectures. Directly relevant to the pitfall in Section 5 of this chapter.

13. J. Hoydis, S. ten Brink, and M. Debbah, Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need?, 2013

    Early massive MIMO performance analysis. Section VI presents measurement-based validation comparing i.i.d. and correlated channel models for 128-antenna systems. Quantifies the capacity overestimation from i.i.d. model assumption.

14. D.-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, Fading Correlation and Its Effect on the Capacity of Multielement Antenna Systems, 2000

    One of the first papers to systematically analyze the effect of spatial correlation on MIMO capacity. Introduces the one-ring model for MIMO systems and shows the capacity reduction under correlated fading.

15. J. G. Proakis and M. Salehi, Digital Communications, McGraw-Hill, 5th ed., 2008

    Chapter 14 covers fading channel models including Rayleigh and Ricean distributions. Good background reference for the historical context of Rayleigh fading (Section 1 of this chapter).

Further Reading

• Rigorous proof of the Marchenko–Pastur law and random matrix theory for wireless

  Couillet & Debbah, *Random Matrix Methods for Wireless Communications*, Chapters 1–3 (Cambridge, 2011)

  The Marchenko–Pastur result stated in Theorem 1 (and used throughout massive MIMO analysis) is proven rigorously here via Stieltjes transforms. Chapter 3 extends to MIMO capacity. Graduate-level probability is required.

• Complete treatment of the one-ring model and JSDM framework

  Adhikary, Nam, Ahn & Caire, 'Joint Spatial Division and Multiplexing,' IEEE Trans. IT, 2013

  This paper fully develops the one-ring model from a precoding design perspective, showing exactly which conditions on angular spreads enable the JSDM two-stage beamforming. The analysis in Sections II–IV is essential preparation for Chapter 7.

• Comprehensive survey of mmWave channel measurements and models

  Rappaport et al., *Millimeter Wave Wireless Communications*, Prentice Hall, 2014 — Chapters 3–5

  Goes far beyond the summary in Section 5, presenting measurement campaigns at 28/38/60/73 GHz, statistical path loss models, and the implications for system design. Authoritative reference from the NYU Wireless group.

• QuaDRiGa channel simulator documentation and tutorial

  QuaDRiGa website https://quadriga-channel-model.de — Tutorial and technical report

  The QuaDRiGa documentation explains in detail how to generate TR 38.901 channels with spatial consistency and dual mobility. The tutorial is hands-on and directly applicable to implementing channel simulations for Chapters 3–7.

• Deep dive into spatial consistency and non-stationarity for XL-MIMO

  De Carvalho et al., 'Non-Stationarities in Extra-Large Scale Massive MIMO,' IEEE Wireless Commun. Lett., 2020

  When the array aperture grows beyond 1 m (Chapter 17: XL-MIMO), the one-ring model breaks down: different antenna elements 'see' different scattering environments. This paper introduces the visibility region (VR) model that extends the channel models of this chapter to the near-field and non-stationary regime.

• Spectral efficiency under realistic 3GPP channel models vs. i.i.d. assumptions

  Hoydis, ten Brink & Debbah, 'Massive MIMO in the UL/DL of Cellular Networks,' IEEE JSAC, 2013

  Provides a direct numerical comparison of i.i.d. vs. correlated channel model predictions for achievable sum-rate in massive MIMO, answering the practical question: 'How much does the model assumption matter?' The measurement validation in Section VI is particularly valuable.