Feedback Control via Integrated Sensing and Communication: Uncertainty Optimisation

Fuente: arXiv
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Autores principales: Soleymani, Touraj, Assaad, Mohamad, Baras, John S.
Formato: Preprint
Publicado: 2026
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author Soleymani, Touraj
Assaad, Mohamad
Baras, John S.
author_facet Soleymani, Touraj
Assaad, Mohamad
Baras, John S.
contents This paper studies strategic design in an integrated sensing and communication (ISAC) architecture for feedback control of cyber-physical systems. We focus on a setting in which the regulation of a physical process (i.e., remote source) is performed via an ISAC-enabled base station. The base station can alternate between tracking the state of the source and delivering control-relevant information back to the source. For a Gauss-Markov source subject to i.i.d. Bernoulli sensing and communication links, under a finite-horizon linear-quadratic-Gaussian cost, we rigorously characterise the optimal policies through an uncertainty-aware synthesis. We establish that the optimal switching policy, for the ISAC system at the base station, is threshold-based in terms of the source and base-station estimation covariances, while the optimal control policy, for the actuator at the source, is linear in the source state estimate. We show that the threshold region$\unicode{x2014}$defined as the set of estimation covariance pairs for which communication is preferred over sensing$\unicode{x2014}$expands with increasing source uncertainty and contracts with increasing base-station uncertainty.
format Preprint
id arxiv_https___arxiv_org_abs_2601_22912
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Feedback Control via Integrated Sensing and Communication: Uncertainty Optimisation
Soleymani, Touraj
Assaad, Mohamad
Baras, John S.
Information Theory
Optimization and Control
This paper studies strategic design in an integrated sensing and communication (ISAC) architecture for feedback control of cyber-physical systems. We focus on a setting in which the regulation of a physical process (i.e., remote source) is performed via an ISAC-enabled base station. The base station can alternate between tracking the state of the source and delivering control-relevant information back to the source. For a Gauss-Markov source subject to i.i.d. Bernoulli sensing and communication links, under a finite-horizon linear-quadratic-Gaussian cost, we rigorously characterise the optimal policies through an uncertainty-aware synthesis. We establish that the optimal switching policy, for the ISAC system at the base station, is threshold-based in terms of the source and base-station estimation covariances, while the optimal control policy, for the actuator at the source, is linear in the source state estimate. We show that the threshold region$\unicode{x2014}$defined as the set of estimation covariance pairs for which communication is preferred over sensing$\unicode{x2014}$expands with increasing source uncertainty and contracts with increasing base-station uncertainty.
title Feedback Control via Integrated Sensing and Communication: Uncertainty Optimisation
topic Information Theory
Optimization and Control
url https://arxiv.org/abs/2601.22912