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Unified performance theory for ISAC (information and estimation)

Establish a universal theoretical framework to jointly evaluate sensing and communication performance in integrated sensing and communication (ISAC) systems by rigorously integrating results from information theory (e.g., mutual information, capacity) and estimation theory (e.g., Fisher information, Cramér–Rao bounds), so that dual-function tradeoffs and resource allocations can be consistently analyzed within a single theory.

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Background

In ISAC systems, performance is typically evaluated with separate metrics from information theory for communications and estimation theory for sensing, complicating joint design and analysis.

The paper highlights that current work treats sensing-oriented, communication-oriented, or joint formulations but lacks a single unifying theory that captures both under a common framework.

A unified theory would streamline tradeoff analysis, enable principled resource allocation across time/frequency/space/power/code, and provide consistent performance bounds for dual-function systems.

References

Note that it remains an open challenge to establish a universal theoretical framework to jointly evaluate the performance of dual-functions in ISAC systems, which can integrate the classical results derived from information theory and estimation theory, respectively.

— The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications (2405.01816 - González-Prelcic et al., 3 May 2024) in Resource allocation, Problem formulations (Section: Waveforms, resource allocation and channel parameter estimation in ISAC networks)