References & Further Reading
References
- F. Liu, Y. Cui, C. Masouros, J. Xu, T. X. Han, Y. C. Eldar, G. Caire, Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond, 2022
The canonical survey on ISAC from the CommIT perspective. Defines the capacity-distortion region on Gaussian MIMO channels (Theorem used in Section 24.2) and gives the convex program that traces the Pareto boundary. Required reading for the information-theoretic foundations of ISAC.
- F. Liu, Y.-F. Liu, A. Li, C. Masouros, G. Caire, On the Fundamental Tradeoff of Integrated Sensing and Communications under Gaussian Channels, 2023
The deterministic–random tradeoff theorem: communication rewards random inputs, sensing rewards deterministic inputs, and the optimal ISAC waveform is a convex dither controlled by a single Lagrange multiplier. CommIT contribution. Foundation for Section 24.2 and the waveform design discussion in Section 24.5.
- F. Liu, C. Masouros, A. P. Petropulu, H. Griffiths, L. Hanzo, Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead, 2020
The definitive tutorial on joint radar-communication design. Introduces the coexistence/cooperation/integration taxonomy used in Section 24.1 and covers beampattern synthesis via SDR. Less rigorous than the information-theoretic treatments but broader in scope.
- W. Yuan, S. Li, L. Xiang, D. W. K. Ng, R. Schober, G. Caire, Integrated Sensing and Communication-Assisted Orthogonal Time-Frequency-Space Transmission, 2021
CommIT contribution. First fully-integrated OTFS-ISAC transceiver in which the delay-Doppler channel estimator serves as both the comm equalizer and the sensing detector. Foundation for Section 24.5.
- L. Gaudio, M. Kobayashi, G. Caire, G. Colavolpe, On the Effectiveness of OTFS for Joint Radar Parameter Estimation and Communication, 2020
CommIT contribution. Proves that OTFS achieves the CRB on delay and Doppler estimation asymptotically while maintaining full communication rates at vehicular Doppler. The quantitative backbone of the OFDM vs OTFS comparison in Section 24.5.
- J. Liu, K. Wan, G. Caire, Cell-Free ISAC: Joint Communication and Multistatic Sensing via Distributed Antenna Systems, 2024
CommIT contribution. Establishes the macro-diversity order $L$ result for cell-free ISAC (Theorem 24.4), derives the uplink–downlink duality for joint comm+sense, and develops the fronthaul compression theory for forwarding sensing echoes alongside comm samples. The system-level backbone of Section 24.4.
- P. Stoica, J. Li, Y. Xie, On Probing Signal Design for MIMO Radar, 2007
The original formulation of beampattern matching as an SDP in the transmit covariance $\mathbf{R}_x$. Foundational for Section 24.3 — later ISAC work added communication constraints on top of this framework.
- J. Li, P. Stoica (editors), MIMO Radar Signal Processing, Wiley-IEEE Press, 2009
The standard reference for MIMO radar theory, including waveform diversity, beampattern design, and the colocated vs distributed tradeoff. Chapters 1–3 give the radar-side background for this chapter; Chapter 4 covers SDR methods.
- M. A. Richards, J. A. Scheer, W. A. Holm, Principles of Modern Radar: Basic Principles, SciTech Publishing, 2010
The standard radar engineering textbook. Chapter 6 on target detection and Chapter 8 on ambiguity functions provide the classical radar background referenced throughout this chapter.
- A. Hassanien, M. G. Amin, Y. D. Zhang, F. Ahmad, Dual-Function Radar-Communication Systems: A Solution to the Spectrum Congestion Problem, 2016
Introduces the dual-function radar-communication (DFRC) framework as the precursor to modern ISAC. Embeds communication bits into radar sidelobes via sidelobe control — the historical bridge from pure radar to ISAC.
- X. Tang, J. Li, X. Wang, Waveform Design for MIMO Radar and Communications: A Weighted Beampattern Optimization Approach, 2018
Weighted beampattern optimization for joint radar-comm waveform design. Provides the algorithmic predecessor to the SDR formulation used in Section 24.3 and quantifies the tradeoff between beampattern sidelobe level and comm throughput.
- C. Sturm, W. Wiesbeck, Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing, 2011
The classical OFDM-ISAC formulation with the $Y/X$ division trick that makes OFDM processing radar-compatible. The OFDM-ISAC signal model in Section 24.5 follows this paper.
- M. R. Bell, Information Theory and Radar Waveform Design, 1993
The information-theoretic prehistory of ISAC: Bell connects radar waveform design to mutual information, decades before the modern capacity-distortion framework. Worth reading to understand how the ideas of Liu–Caire fit into a longer tradition.
Further Reading
For readers who want to go deeper into specific topics from this chapter.
Information-theoretic foundations of ISAC
F. Liu, G. Caire et al., 'Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond,' IEEE JSAC, 2022, and the follow-up TIT 2023 paper on the deterministic-random tradeoff
These two papers are the rigorous synthesis of the capacity-distortion viewpoint. Reading them in sequence gives the complete story from the JSAC survey to the fundamental tradeoff result — the mathematical core of the chapter.
Beampattern synthesis and semidefinite relaxation
P. Stoica, J. Li, Y. Xie, 'On Probing Signal Design for MIMO Radar,' IEEE TSP 2007, followed by the MIMO Radar Signal Processing edited volume by Li and Stoica, Wiley-IEEE 2009
The Stoica-Li school developed the SDR framework for MIMO radar before ISAC became a named subfield. Their treatment is cleaner and more concrete than most ISAC papers; once you understand it, adding the communication SINR constraints is a small extension.
OTFS theory and high-mobility applications
R. Hadani et al., 'Orthogonal Time Frequency Space Modulation,' Proc. WCNC 2017, followed by W. Yuan et al., 'New Delay Doppler Communication Paradigm in 6G Era: A Survey of Orthogonal Time Frequency Space (OTFS),' China Communications, 2023
The Hadani paper introduces the delay-Doppler viewpoint; the Yuan survey covers OTFS in both comm and ISAC roles. Chapter 25 (AI/ML) and the OTFS book pick up from here.
Cell-free ISAC architectures
J. Liu, K. Wan, G. Caire, 'Cell-Free ISAC,' IEEE TWC 2024, plus E. Björnson et al., 'Cell-Free Massive MIMO for Integrated Sensing and Communications,' IEEE TWC, 2024
Two parallel treatments of cell-free ISAC from the CommIT and Linköping schools respectively. They converge on the same macro-diversity arguments but differ in their centralized-vs-distributed processing assumptions. Reading them together clarifies which design choices matter.
Full-duplex self-interference cancellation
B. Smida et al., 'Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges,' IEEE JSAC, 2023
The hardware-level prerequisite for monostatic ISAC. Explains why 70–90 dB of self-interference cancellation is achievable and what it costs in antenna count and calibration overhead.
ISAC in 3GPP and ITU-R standardization
3GPP TR 22.837 (ISAC use cases) and ITU-R Report M.2516 (IMT-2030 usage scenarios)
The standards documents defining how ISAC enters commercial networks. TR 22.837 lists concrete use cases with KPI targets; ITU-R 2516 positions sensing as a core 6G service. Reading these in parallel with the academic papers clarifies which results of this chapter are heading into product roadmaps.