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

arXiv: https://arxiv.org/abs/2507.08164 · HTML: https://mlsanity.com/paper/2507.08164/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Agentic AI for wireless networks, one of 16 directions in LLM agents and tool use.
- Builds on 11 of its 25 references that are in the map.
- First posted on arXiv 10 Jul 2025.

## Placed in

- LLM agents and tool use / [Agentic AI for wireless networks](https://mlsanity.com/agents/agentic-ai-for-wireless-networks/)

## Builds on (most cited first, 11 of 11)

- [Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering](https://mlsanity.com/paper/2404.17723/) (2024)
- [GRAG: Graph Retrieval-Augmented Generation](https://mlsanity.com/paper/2405.16506/) (2024)
- [Large Language Model Enhanced Multi-Agent Systems for 6G Communications](https://mlsanity.com/paper/2312.07850/) (2023)
- [WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks](https://mlsanity.com/paper/2505.01074/) (2025)
- [Large Language Models for Zero Touch Network Configuration Management](https://mlsanity.com/paper/2408.13298/) (2024)
- [Knowledge-Defined Networking](https://mlsanity.com/paper/1606.06222/) (2016)
- [6G comprehensive intelligence: network operations and optimization based on Large Language Models](https://mlsanity.com/paper/2404.18373/) (2024)
- [Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysis](https://mlsanity.com/paper/2406.18114/) (2024)
- [Automatic Retrieval-augmented Generation of 6G Network Specifications for Use Cases](https://mlsanity.com/paper/2405.03122/) (2024)
- [Toward Generative 6G Simulation: An Experimental Multi-Agent LLM and ns-3 Integration](https://mlsanity.com/paper/2503.13402/) (2025)
- [Building AI Service Repositories for On-Demand Service Orchestration in 6G AI-RAN](https://mlsanity.com/paper/2504.09647/) (2025)

## Built on by (most cited first, 1 of 1)

- [SoK: Semantic Decision Engines in Network Control Loops](https://mlsanity.com/paper/2610.06425/) (2026)

## Abstract (arXiv)

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.