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arXiv · 2507.08164

KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence

Yun Tang·Mengbang Zou·Zeinab Nezami·Syed Ali Raza Zaidi·Weisi Guo
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Abstract

The emergence of large language models (LLMs) and agentic systems is enabling autonomous 6G networks with advanced intelligence, including self-configuration, self-optimization, and self-healing. However, the current implementation of individual intelligence tasks necessitates isolated knowledge retrieval pipelines, resulting in redundant data flows and inconsistent interpretations. Inspired by the service model unification effort in Open-RAN (to support interoperability and vendor diversity), we propose KP-A: a unified Network Knowledge Plane specifically designed for Agentic network intelligence. By decoupling network knowledge acquisition and management from intelligence logic, KP-A streamlines development and reduces maintenance complexity for intelligence engineers. By offering an intuitive and consistent knowledge interface, KP-A also enhances interoperability for the network intelligence agents. We demonstrate KP-A in two representative intelligence tasks: live network knowledge Q&A and edge AI service orchestration. All implementation artifacts have been open-sourced to support reproducibility and future standardization efforts.

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Yun Tang, Mengbang Zou, Zeinab Nezami, Syed Ali Raza Zaidi, Weisi Guo. 2025-07-10. KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence. https://arxiv.org/abs/2507.08164

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