References & Further Reading

References

  1. E. Bjornson, J. Hoydis, and L. Sanguinetti, Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency, Foundations and Trends in Signal Processing, vol. 11, no. 3--4, 2017

    The definitive monograph on massive MIMO. Chapters 3--4 cover MRT, ZF, and MMSE precoding with detailed achievable rate analysis under imperfect CSI. Available open access.

  2. M. Joham, W. Utschick, and J. A. Nossek, Linear Transmit Processing in MIMO Communications Systems, 2005

    Derives MRT, ZF, and MMSE precoding from unified optimization criteria. The MMSE transmit filter derivation is the origin of RZF precoding.

  3. C. B. Peel, B. M. Hochwald, and A. L. Swindlehurst, A Vector-Perturbation Technique for Near-Capacity Multiantenna Multiuser Communication — Part I: Channel Inversion and Regularization, 2005

    Introduces regularized channel inversion (RZF) and derives the optimal regularization parameter. Part II develops the nonlinear vector perturbation technique.

  4. Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, Zero-Forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels, 2004

    Systematic treatment of block diagonalisation and ZF precoding for the MU-MIMO downlink, including the multi-antenna user case.

  5. H. Weingarten, Y. Steinberg, and S. S. Shamai (Shitz), The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel, 2006

    The landmark paper proving that DPC with Gaussian codebooks achieves the MIMO BC capacity region. Settles the BC capacity conjecture.

  6. S. Vishwanath, N. Jindal, and A. Goldsmith, Duality, Achievable Rates, and Sum-Rate Capacity of Gaussian MIMO Broadcast Channels, 2003

    Establishes MAC-BC duality and shows DPC achievability for the MIMO BC. Together with Weingarten et al. (2006), completes the BC capacity proof.

  7. M. H. M. Costa, Writing on Dirty Paper, 1983

    The original dirty-paper coding result: the capacity of a channel with known interference equals the capacity without interference. The foundation for DPC-based MIMO BC capacity.

  8. T. K. Y. Lo, Maximum Ratio Transmission, 1999

    Formalises MRT as the transmit-side dual of MRC. Shows that MRT maximises the SNR at the intended receiver.

  9. A. Wiesel, Y. C. Eldar, and S. S. Shamai (Shitz), Zero-Forcing Precoding and Generalized Inverses, 2008

    Comprehensive treatment of ZF precoding with per-antenna power constraints, generalized inverses, and the SOCP formulation.

  10. S. Wagner, R. Couillet, M. Debbah, and D. T. M. Slock, Large System Analysis of Linear Precoding in Correlated MISO Broadcast Channels Under Limited Feedback, 2012

    Provides deterministic equivalents for the SINR of ZF and RZF precoding in the large-system regime, enabling closed-form performance analysis.

  11. W. Yu and T. Lan, Transmitter Optimization for the Multi-Antenna Downlink with Per-Antenna Power Constraints, 2007

    Extends MAC-BC duality to per-antenna power constraints, showing that the dual uplink has a diagonal noise covariance.

  12. G. Caire, On the Ergodic Rate Lower Bounds with Applications to Massive MIMO, 2018

    Shows that massive MIMO has unlimited capacity even with pilot contamination when spatial correlation is exploited. Foundation for the claim that linear precoding suffices in the massive regime.

  13. T. L. Marzetta, E. G. Larsson, H. Yang, and H. Q. Ngo, Fundamentals of Massive MIMO, Cambridge University Press, 2016

    The first textbook on massive MIMO. Chapters 3--4 provide an accessible introduction to MRT, ZF, and MMSE processing.

Further Reading

Resources for deeper exploration of linear precoding and its extensions.

  • Nonlinear precoding: vector perturbation and Tomlinson--Harashima

    Peel, Hochwald, and Swindlehurst (2005), Part II

    Goes beyond linear precoding to near-capacity nonlinear techniques. Vector perturbation closes part of the gap to DPC.

  • Massive MIMO with correlated channels

    Bjornson, Hoydis, and Sanguinetti (2017), Chapter 7

    Extends the analysis to spatially correlated channels where the channel covariance affects both the optimal precoder and the achievable rates.

  • Iterative precoding algorithms for PAPC

    Wiesel, Eldar, and Shamai (2008)

    Detailed algorithms for ZF and RZF under per-antenna constraints, including SOCP formulations and convergence guarantees.

  • Random matrix theory for MIMO

    Couillet and Debbah, Random Matrix Methods for Wireless Communications, 2011

    Provides the mathematical tools (Stieltjes transforms, deterministic equivalents) for the large-system analysis used in this chapter.

ExercisesCh 7 →