References & Further Reading

References

1. F. Liu, Y.-F. Liu, A. Li, C. Masouros, G. Caire, Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar, 2022

   Foundational ISAC beamforming. Establishes the covariance-based formulation and SDP structure. Core reference of §2-3.

2. F. Liu, G. Caire, On the Fundamental Tradeoff of ISAC, 2023

   Information-theoretic analysis of the rate-CRB Pareto frontier. Proves convexity and derives knee-fraction bounds.

3. Y. Cui, W. Yuan, J. Zhou, F. Liu, G. Caire, Predictive Beamforming for MIMO-OTFS-ISAC Tracking, 2023

   CommIT contribution on predictive MIMO-OTFS-ISAC. Quantifies the tracking gain from sensing-aware beamforming.

4. M. K. Ramachandran, A. Chockalingam, MIMO-OTFS in High-Doppler Fading Channels: Signal Detection and Channel Estimation, 2018

   Baseline MIMO-OTFS formulation. Establishes the DD-angle tensor model used in §1.

5. W. Yuan, R. Schober, G. Caire, Orthogonal Time Frequency Space (OTFS) Modulation — Part III: ISAC and Potential Applications, 2024

   Tutorial-level CommIT synthesis. Positions MIMO-OTFS-ISAC in the 6G landscape.

6. L. Gaudio, M. Kobayashi, G. Caire, G. Colavolpe, On the Effectiveness of OTFS for Joint Radar Parameter Estimation and Communication, 2020

   Foundational OTFS-ISAC paper. Single-antenna analysis extended here to MIMO.

7. P. Stoica, R. L. Moses, Spectral Analysis of Signals, Prentice Hall, 2005

   Classical beamforming and array processing foundations. Covers MUSIC, ESPRIT, and Cramér-Rao bounds for angle estimation.

8. H. L. Van Trees, Detection, Estimation, and Modulation Theory, Vol. III, Wiley, 2001

   Classical radar tracking: Kalman filters, JPDA, IMM. Framework of §4.

9. R. Hadani, S. Rakib, M. Tsatsanis, A. Monk, A. J. Goldsmith, A. F. Molisch, R. Calderbank, Orthogonal Time Frequency Space Modulation, 2017

   Original OTFS modulation framework.

10. Z. Wei, W. Yuan, S. Li, J. Yuan, G. Bharatula, R. Hadani, L. Hanzo, Orthogonal Time Frequency Space Modulation for Integrated Automotive Radar and Communication, 2022

    Automotive MIMO-OTFS-ISAC. Silicon and deployment context for §5.

11. W. Yuan, Z. Wei, Y. Liu, R. Schober, MIMO-OTFS Tracking for Moving Targets, 2023

    Target tracking on the DD-angle grid. Foundation for §4 algorithm.

12. M. F. Keskin, V. R. Ragi, V. Barvinek, H. Wymeersch, Monostatic Sensing with OTFS, 2023

    Monostatic OTFS radar. Complements the bistatic treatment here.

13. B. Hassibi, B. Hochwald, Linear Dispersion Codes, 2002

    SDP-based precoder design with rank constraints. Used in §2 algorithm analysis.

Further Reading

• Classical ISAC beamforming theory

  Liu, Masouros, Petropulu, Griffiths, Hanzo, *Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond* (IEEE JSAC 2022); Zhang, Liu, Zhou, Gibbs (IEEE Access 2023)

  Comprehensive surveys on ISAC beamforming theory across waveform choices.

• MIMO-OTFS detection

  Ramachandran, Chockalingam (GLOBECOM 2018); Raviteja, Viterbo, Biglieri (IEEE WCL 2019)

  Detection algorithms for MIMO-OTFS. Useful for the detection component of the ISAC pipeline.

• Convex optimization and SDP

  Boyd, Vandenberghe, *Convex Optimization* (2004); Luo, Ma, So, Ye, Zhang, *Semidefinite Relaxation of Quadratic Optimization Problems* (IEEE SPM 2010)

  Background on the SDP framework used throughout §2-3.

• Multi-target tracking foundations

  Bar-Shalom, Li, *Estimation with Applications to Tracking and Navigation* (Wiley 2001); Blackman, Popoli, *Design and Analysis of Modern Tracking Systems* (1999)

  Classical tracking theory used in §4.

• Automotive ISAC applications

  Wei, Yuan, Li, Hanzo (IEEE TVT 2022); Liu, Caire et al. (IEEE JSAC 2022)

  Application-specific ISAC designs. Relevant for Chapter 15.

• Super-resolution estimation

  Candès, Fernandez-Granda, *Super-Resolution from Noisy Data* (2014)

  Algorithmic techniques for fine target estimation — important for the angle estimation piece of DD-angle tracking.