On the Fundamental Tradeoff of Joint Communication and QCD: The Monostatic Case

2025-12-09

AI Summary

This paper investigates the fundamental trade-off between communication rate and quickest change detection (QCD) performance in monostatic integrated sensing and communication (ISAC) systems under dynamic channels and unknown abrupt changes. To address this, we propose a feedback-based Joint Communication and Change-Structure (JCCS) coding strategy, which dynamically adapts encoding parameters via real-time channel state estimation, sub-block coding, and state-dependent modeling of mutual information and KL divergence. We prove that the proposed QCD algorithm is asymptotically optimal and, for the first time, characterize the achievable rate–detection-delay region. Numerical evaluations on binary and MIMO Gaussian channels demonstrate JCCS’s significant gains in reducing detection delay while maintaining communication reliability. The work provides both foundational theoretical insights and a practical coding framework for the co-design of ISAC systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

This paper investigates the fundamental tradeoff between communication and quickest change detection (QCD) in integrated sensing and communication (ISAC) systems under a monostatic setup. We introduce a novel Joint Communication and quickest Change subblock coding Strategy (JCCS) that leverages feedback to adapt coding dynamically based on real-time state estimation. The achievable rate-delay region is characterized using state-dependent mutual information and KL divergence, providing a comprehensive framework for analyzing the interplay between communication performance and detection delay. Moreover, we provide a partial converse demonstrating the asymptotic optimality of the proposed detection algorithm within the JCCS framework. To illustrate the practical implications, we analyze binary and MIMO Gaussian channels, revealing insights into achieving optimal tradeoffs in ISAC system design.

Problem

• Investigates tradeoff between communication and quickest change detection in ISAC systems
• Characterizes achievable rate-delay region using state-dependent mutual information
• Analyzes binary and MIMO Gaussian channels for optimal ISAC design tradeoffs

Innovation

• Novel JCCS strategy uses feedback for dynamic coding
• Achievable rate-delay region characterized via mutual information
• Asymptotic optimality shown for detection algorithm in JCCS