References & Further Reading

References

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

    The foundational textbook on massive MIMO. Chapters 3–4 develop the linear receiver analysis (MRC, ZF, MMSE) and the asymptotic SINR expressions used throughout this chapter.

  2. E. Bjornson, J. Hoydis, and L. Sanguinetti, Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency, Foundations and Trends in Signal Processing, 2017

    Comprehensive monograph on massive MIMO performance analysis. Chapter 3 provides the SINR expressions and comparison tables used here. Freely available online.

  3. D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press, 2005

    Chapter 8 treats MIMO detection from first principles: linear receivers, V-BLAST/SIC, and the connection to the MAC capacity region.

  4. A. El Gamal and Y.-H. Kim, Network Information Theory, Cambridge University Press, 2011

    Chapter 4 gives the rigorous information-theoretic treatment of the MAC capacity region and successive decoding.

  5. S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall, 1993

    Chapter 12 derives the LMMSE estimator used as the foundation for the MMSE receiver. The connection between estimation and detection is central to this chapter.

  6. R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, 2nd ed., 2012

    Reference for the matrix inversion lemma, condition number analysis, and eigenvalue inequalities used in the ZF and MMSE derivations.

  7. M. Wu, B. Yin, A. Vosoughi, C. Studer, J. R. Cavallaro, and C. Dick, Approximate Matrix Inversion for High-Throughput Data Detection in the Large-Scale MIMO Uplink, 2014

    Proposes the Neumann series approximation for massive MIMO detection and analyzes convergence as a function of the antenna-to-user ratio.

  8. S. Jacobsson, G. Durisi, M. Coldrey, U. Gustavsson, and C. Studer, Throughput Analysis of Massive MIMO Uplink with Low-Resolution ADCs, 2017

    Comprehensive analysis of quantized massive MIMO detection using the Bussgang decomposition. Derives the box detector and rate expressions for arbitrary ADC resolution.

  9. J. J. Bussgang, Crosscorrelation Functions of Amplitude-Distorted Gaussian Signals, 1952

    The original paper establishing the Bussgang decomposition for nonlinear transformations of Gaussian signals. Rediscovered by the massive MIMO community for low-resolution ADC analysis.

  10. G. L. Turin, An introduction to matched filters, 1960

    Classic reference on matched filtering and its SNR-maximizing property. The MRC receiver is the spatial matched filter.

  11. G. J. Foschini, Layered Space-Time Architecture for Wireless Communication in a Fading Environment When Using Multi-Element Antennas, 1996

    Introduced the BLAST architecture using SIC detection for spatial multiplexing — the precursor to massive MIMO uplink detection.

  12. S. Verdu, Multiuser Detection, Cambridge University Press, 1998

    Comprehensive treatment of multiuser detection theory including decorrelator (ZF), MMSE, and SIC receivers. The theoretical foundation for all receivers in this chapter.

Further Reading

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

  • Optimal decoding order for MMSE-SIC

    Verdu, *Multiuser Detection*, Ch. 6

    Derives the optimal ordering (decode weakest user first) for minimizing error propagation, and analyzes the gap between optimal and suboptimal orderings.

  • Low-resolution ADC architectures

    Jacobsson et al., 'Quantized Precoding for Massive MU-MIMO,' IEEE Trans. Commun., 2017

    Extends the Bussgang framework to the downlink and analyzes mixed-ADC architectures where a few high-resolution ADCs are combined with many 1-bit units.

  • Iterative detection for massive MIMO

    Yin et al., 'Conjugate gradient-based soft-output detection and precoding in massive MIMO systems,' IEEE GLOBECOM, 2014

    Compares CG, Neumann, and Jacobi iterative methods for massive MIMO detection, including FPGA implementation results showing real-time operation at 128 antennas.

  • Detection with imperfect CSI

    Bjornson et al., *Massive MIMO Networks*, Ch. 4

    Combines the receiver analysis from this chapter with the channel estimation analysis from MIMO Ch. 3 via the use-and-then-forget bound to derive realistic achievable rates.

  • Near-optimal nonlinear detection

    Choi et al., 'Near-ML performance achieving low-complexity detection for MIMO systems,' IEEE GLOBECOM, 2005

    For systems where the linear receivers are insufficient (low $\ntn{ntx}/\ntn{nusers}$ ratio), describes lattice-reduction-aided detection that approaches ML performance at polynomial complexity.

ExercisesCh 10 →