Sensing With Communication Signals: From Information Theory to Signal Processing

2025-02-15

AI Summary

To meet 6G integrated sensing and communication (ISAC) requirements, this work addresses the fundamental challenge of jointly optimizing sensing and communication performance using stochastic communication signals. Method: We propose a novel deterministic–randomness trade-off (DRT) theoretical framework to establish performance bounds on the average autocorrelation function (ACF) of random ISAC signals; introduce a communication-prioritized joint design principle for modulation, constellation, and pulse shaping; and develop an end-to-end ISAC processing pipeline tailored to stochastic signals. Contribution/Results: Through information-theoretic analysis, stochastic signal modeling, and multi-objective ranging performance evaluation, we characterize the theoretical limits of high-precision sensing with random waveforms, derive scalable sensing–communication performance trade-off criteria, and provide a methodology for ISAC signal design and processing that balances theoretical rigor with engineering feasibility for 6G systems.

Technology Category

• Reasoning under Uncertainty: Stochastic Optimization
• 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
• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

The Integrated Sensing and Communications (ISAC) paradigm is anticipated to be a cornerstone of the upcoming 6G networks. In order to optimize the use of wireless resources, 6G ISAC systems need to harness the communication data payload signals, which are inherently random, for both sensing and communication (S&C) purposes. This tutorial paper provides a comprehensive technical overview of the fundamental theory and signal processing methodologies for ISAC transmission with random communication signals. We begin by introducing the deterministic-random tradeoff (DRT) between S&C from an information-theoretic perspective, emphasizing the need for specialized signal processing techniques tailored to random ISAC signals. Building on this foundation, we review the core signal models and processing pipelines for communication-centric ISAC systems, and analyze the average squared auto-correlation function (ACF) of random ISAC signals, which serves as a fundamental performance metric for multi-target ranging tasks. Drawing insights from these theoretical results, we outline the design principles for the three key components of communication-centric ISAC systems: modulation schemes, constellation design, and pulse shaping filters. The goal is to either enhance sensing performance without compromising communication efficiency or to establish a scalable tradeoff between the two. We then extend our analysis from a single-antenna ISAC system to its multi-antenna counterpart, discussing recent advancements in multi-input multi-output (MIMO) precoding techniques specifically designed for random ISAC signals. We conclude by highlighting several open challenges and future research directions in the field of sensing with communication signals.

Problem

• Optimize wireless resources in 6G ISAC
• Develop signal processing for random ISAC signals
• Enhance sensing without compromising communication efficiency

Innovation

• ISAC transmission with random signals
• MIMO precoding for ISAC
• DRT theory for S&C optimization