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PCDT: A Predictive Cognitive Digital Twin Framework for Intelligent and Autonomous 6G Network Ecosystems — arXiv:2610.09546

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.09546
License (as archived): CC0-1.0
Archived: 2026-10-08T12:37:55.429Z
SHA-256 of the archived text: de1c06c1524b047866c4fbeb79d692146fb69ae54bcf7051b70f91d5c3546979
Stable URL of this page: https://metraipolis.com/documento/dc_e9f89fa22016

How to cite

PCDT: A Predictive Cognitive Digital Twin Framework for Intelligent and Autonomous 6G Network Ecosystems — arXiv:2610.09546 — arXiv (en), https://arxiv.org/abs/2610.09546 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e9f89fa22016 (Metraipolis archive dc_e9f89fa22016, sha256 de1c06c1524b047866c4fbeb79d692146fb69ae54bcf7051b70f91d5c3546979)

BibTeX

@misc{dce9f89fa22016,
  title = {PCDT: A Predictive Cognitive Digital Twin Framework for Intelligent and Autonomous 6G Network Ecosystems — arXiv:2610.09546},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.09546},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e9f89fa22016; sha256 de1c06c1524b047866c4fbeb79d692146fb69ae54bcf7051b70f91d5c3546979},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.09546. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Future 6G networks are expected to operate as intelligent and autonomous ecosystems where monitoring, prediction, and control are integrated into continuous self-optimization loops. However, many digital-twin-based network management approaches still act mainly as synchronized replicas of the network. They observe the state, report degradation, and trigger corrective action only after performance risk has appeared. This leaves a gap between the vision of a cognitive digital twin (CDT) and the behavior of conventional reactive control loops. In this paper, we propose a Predictive Cognitive Digital Twin (PCDT) framework that closes the loop from observation to predictive cognition to proactive resource control. PCDT maintains a persistent traffic world model, forecasts near-future load, and allocates capacity for the predicted horizon peak before a Service Level Agreement (SLA) violation occurs. Evaluated on a real-world traffic trace, PCDT achieves the lowest allocation error among all benchmarked baseline frameworks, reducing MAE by 43% and RMSE by 32% relative to the best baseline (reactive control). Relative to the threshold heuristic, the only baseline with zero violations, PCDT reduces mean allocated capacity by 50%, reconfiguration churn by 56%, and total operating cost by 50%, indicating substantially more efficient performance. These results show the proposed framework advances the digital twin (DT) operation mechanism from a passive representation towards a cognitive, proactive control, and "intent-aware" mechanism aligned with autonomous 6G network vision.

Tema degli esploratori: calcolo e infrastrutture (elenco arXiv cs.NI, nuovi lavori del giorno).
Categorie arXiv: Networking and Internet Architecture (cs.NI).
Pagina del lavoro: https://arxiv.org/abs/2610.09546 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T12:14:45.286Z dalla pagina https://arxiv.org/list/cs.NI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).