[Paper Review] A Survey on Fundamental Limits of Integrated Sensing and Communication

An Liu, Zhe Huang+11 more|arXiv (Cornell University)|Apr 16, 2021

Indoor and Outdoor Localization Technologies20 citations

TL;DR

This paper provides a comprehensive survey on the fundamental limits of integrated sensing and communication (ISAC), proposing a unified classification framework for traditional sensing and ISAC systems. It analyzes performance bounds for sensing and communication metrics, identifies key challenges such as channel estimation errors and synchronization, and outlines open problems for future research in ISAC design and theoretical limits.

ABSTRACT

The integrated sensing and communication (ISAC), in which the sensing and communication share the same frequency band and hardware, has emerged as a key technology in future wireless systems. Early works on ISAC have been focused on the design, analysis and optimization of practical ISAC technologies for various ISAC systems. While this line of works are necessary, it is equally important to study the fundamental limits of ISAC in order to understand the gap between the current state-of-the-art technologies and the performance limits, and provide useful insights and guidance for the development of better ISAC technologies that can approach the performance limits. In this paper, we aim to provide a comprehensive survey for the current research progress on the fundamental limits of ISAC. Particularly, we first propose a systematic classification method for both traditional radio sensing (such as radar sensing and wireless localization) and ISAC so that they can be naturally incorporated into a unified framework. Then we summarize the major performance metrics and bounds used in sensing, communications and ISAC, respectively. After that, we present the current research progresses on fundamental limits of each class of the traditional sensing and ISAC systems. Finally, the open problems and future research directions are discussed.

Motivation & Objective

• To establish a systematic classification framework that unifies traditional radio sensing and ISAC for consistent analysis.
• To summarize major performance metrics and theoretical bounds in sensing, communications, and ISAC systems.
• To investigate the fundamental limits of ISAC under various channel topologies and system models.
• To identify open problems and future research directions, particularly regarding practical impairments like channel estimation error and synchronization.
• To provide a foundation for designing ISAC systems that approach theoretical performance limits by integrating insights from both sensing and communication theory.

Proposed method

• Proposes a four-category classification of ISAC systems: device-free sensing, device-based sensing, device-free ISAC, and device-based ISAC, based on target participation in sensing.
• Introduces abstracted ISAC channel topologies to model diverse system configurations, including IRS-aided and environment side information-aided scenarios.
• Applies information-theoretic tools to derive fundamental performance bounds for sensing parameters (e.g., DOA, delay, velocity) and communication rates.
• Analyzes the impact of practical impairments—such as channel estimation error, frequency offset, and timing synchronization—on fundamental limits.
• Leverages existing tracking theory to model time-varying channel and sensing states under different mobility models.
• Integrates map and environmental side information into the theoretical framework to enhance performance bounds in prior-aware scenarios.

Experimental results

Research questions

• RQ1 How can traditional sensing and ISAC systems be systematically classified to enable unified theoretical analysis?
• RQ2 What are the fundamental performance bounds for key sensing parameters (e.g., DOA, delay, velocity) and communication rates in ISAC systems?
• RQ3 How do practical impairments such as channel estimation error and timing synchronization affect the theoretical limits of ISAC?
• RQ4 What is the role of intelligent reflecting surfaces (IRS) and environment side information in shaping the fundamental limits of ISAC?
• RQ5 How can tracking performance limits be derived for ISAC systems under dynamic mobility conditions?

Key findings

• The fundamental limits of ISAC cannot be obtained by simply combining existing bounds from separate sensing and communication systems.
• IRS-aided ISAC systems offer new degrees of freedom through passive beamforming, leading to fundamentally different performance limits compared to conventional ISAC.
• Channel estimation error, frequency offset, and timing synchronization error significantly degrade sensing accuracy and must be incorporated into theoretical limit analysis.
• Subcentimeter-level positioning accuracy in 6G systems demands nanosecond-level timing synchronization, making synchronization errors a critical performance limiter.
• Environment side information such as map data can be leveraged to improve fundamental performance bounds, requiring new information-theoretic frameworks.
• Tracking performance limits under mobility can be analyzed using state-space models, with stability and bounded error conditions derived for time-varying systems.