Goal-Oriented Access Optimization for ISAC-Enabled Digital Twins

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Saggese, Fabio, Chiariotti, Federico, Pandey, Shashi Raj, Wymeersch, Henk, Sanguinetti, Luca, Popovski, Petar
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866918366314233856
author Saggese, Fabio
Chiariotti, Federico
Pandey, Shashi Raj
Wymeersch, Henk
Sanguinetti, Luca
Popovski, Petar
author_facet Saggese, Fabio
Chiariotti, Federico
Pandey, Shashi Raj
Wymeersch, Henk
Sanguinetti, Luca
Popovski, Petar
contents The digital twins (DTs) of physical systems and environments enable real-time remote tracking, control, and learning, but require low-latency transmission of updates and sensory data to maintain alignment with their physical counterparts. In this context, augmenting sensory data with the network's own integrated sensing and communication (ISAC)capabilities can expand the DT's awareness of the environment by allowing it to precisely non-radar locate measurements from mobile nodes. However, this integration increases the complexity of the communication system, and can only be supported through intelligent resource allocation and access optimization. In this work, we propose a two-step goal-oriented approach to solve this problem: we design a push-based random access in which sensors with a high Value of Information (VoI) inform the network of their access requirements, followed by a pull-based scheduled transmission of the actual sensory data. This design allows to combine the ISAC and reliable transmission requirements and maximize the VoI of the information delivered to the DT, significantly outperforming existing schemes.
format Preprint
id arxiv_https___arxiv_org_abs_2603_01781
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Goal-Oriented Access Optimization for ISAC-Enabled Digital Twins
Saggese, Fabio
Chiariotti, Federico
Pandey, Shashi Raj
Wymeersch, Henk
Sanguinetti, Luca
Popovski, Petar
Signal Processing
The digital twins (DTs) of physical systems and environments enable real-time remote tracking, control, and learning, but require low-latency transmission of updates and sensory data to maintain alignment with their physical counterparts. In this context, augmenting sensory data with the network's own integrated sensing and communication (ISAC)capabilities can expand the DT's awareness of the environment by allowing it to precisely non-radar locate measurements from mobile nodes. However, this integration increases the complexity of the communication system, and can only be supported through intelligent resource allocation and access optimization. In this work, we propose a two-step goal-oriented approach to solve this problem: we design a push-based random access in which sensors with a high Value of Information (VoI) inform the network of their access requirements, followed by a pull-based scheduled transmission of the actual sensory data. This design allows to combine the ISAC and reliable transmission requirements and maximize the VoI of the information delivered to the DT, significantly outperforming existing schemes.
title Goal-Oriented Access Optimization for ISAC-Enabled Digital Twins
topic Signal Processing
url https://arxiv.org/abs/2603.01781