# An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading

arXiv: https://arxiv.org/abs/2602.13227 · HTML: https://mlsanity.com/paper/2602.13227/

## 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 31 references that are in the map.
- First posted on arXiv 27 Jan 2026.

## 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)

- [Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution](https://mlsanity.com/paper/2409.12191/) (2024)
- [LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://mlsanity.com/paper/2403.13372/) (2024)
- [gpt-oss-120b & gpt-oss-20b Model Card](https://mlsanity.com/paper/2508.10925/) (2025)
- [Data-efficient Fine-tuning for LLM-based Recommendation](https://mlsanity.com/paper/2401.17197/) (2024)
- [LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models](https://mlsanity.com/paper/2404.01230/) (2024)
- [Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach](https://mlsanity.com/paper/2402.07573/) (2024)
- [AI-Native Network Slicing for 6G Networks](https://mlsanity.com/paper/2105.08576/) (2021)
- [A Practical Guide for Designing, Developing, and Deploying Production-Grade Agentic AI Workflows](https://mlsanity.com/paper/2512.08769/) (2025)
- [Towards Responsible and Explainable AI Agents with Consensus-Driven Reasoning](https://mlsanity.com/paper/2512.21699/) (2025)
- [Model Context Contracts - MCP-Enabled Framework to Integrate LLMs With Blockchain Smart Contracts](https://mlsanity.com/paper/2510.19856/) (2025)
- [VTutor: An Open-Source SDK for Generative AI-Powered Animated Pedagogical Agents with Multi-Media Output](https://mlsanity.com/paper/2502.04103/) (2025)

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

- [Beyond State Machines: Executing Network Procedures with Agentic Tool-Calling Sequences](https://mlsanity.com/paper/2605.02584/) (2026)

## Abstract (arXiv)

6G networks are expected to be AI-native, intent-driven, and economically programmable, requiring fundamentally new approaches to network slice orchestration. Existing slicing frameworks, largely designed for 5G, rely on static policies and manual workflows and are ill-suited for the dynamic, multi-domain, and service-centric nature of emerging 6G environments. In this paper, we propose an agentic AI control plane architecture for 6G network slice orchestration, monitoring, and trading that treats orchestration as a holistic control function encompassing slice planning, deployment, continuous monitoring, and economically informed decision-making. The proposed control plane is realized as a layered architecture in which multiple cooperating AI agents. To support flexible and on-demand slice utilization, the control plane incorporates market-aware orchestration capabilities, allowing slice requirements, pricing, and availability to be jointly considered during orchestration decisions. A natural language interface, implemented using the Model Context Protocol (MCP), enables users and applications to interact with control-plane functions through intent-based queries while enforcing safety and policy constraints. To ensure responsible and explainable autonomy, the control plane integrates fine-tuned large language models organized as a multi-model consortium, governed by a dedicated reasoning model. The proposed approach is evaluated using a real-world testbed with multiple mobile core instances (e.g Open5GS) integrated with Ericsson's RAN infrastructure. The results demonstrate that combining agentic autonomy, closed-loop SLA assurance, market-aware orchestration, and natural language control enables a scalable and adaptive 6G-native control plane for network slice management, highlighting the potential of agentic AI as a foundational mechanism for future 6G networks.