# Learning Multi-Access Point Coordination in Agentic AI Wi-Fi with Large Language Models

arXiv: https://arxiv.org/abs/2511.20719 · HTML: https://mlsanity.com/paper/2511.20719/

## Key facts

- Cited by 2 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 10 of its 15 references that are in the map.
- First posted on arXiv 25 Nov 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, 10 of 10)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation](https://mlsanity.com/paper/2308.08155/) (2023)
- [Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?](https://mlsanity.com/paper/2202.12837/) (2022)
- [WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks](https://mlsanity.com/paper/2505.01074/) (2025)
- [Large Language Models for Wireless Communications: From Adaptation to Autonomy](https://mlsanity.com/paper/2507.21524/) (2025)
- [What Will Wi-Fi 8 Be? A Primer on IEEE 802.11bn Ultra High Reliability](https://mlsanity.com/paper/2303.10442/) (2023)
- [Throughput Analysis of IEEE 802.11bn Coordinated Spatial Reuse](https://mlsanity.com/paper/2309.09169/) (2023)
- [IEEE 802.11bn Multi-AP Coordinated Spatial Reuse with Hierarchical Multi-Armed Bandits](https://mlsanity.com/paper/2501.03680/) (2025)
- [Hierarchical Multi-Agent Reinforcement Learning-based Coordinated Spatial Reuse for Next Generation WLANs](https://mlsanity.com/paper/2506.14187/) (2025)

## Built on by (most cited first, 2 of 2)

- [E3-Agent: An Executable and Evolving Agent for Resource Management of Edge Generative Inference](https://mlsanity.com/paper/2605.27428/) (2026)
- [FM4WiFi: Flow Matching for Multi-AP Coordination in Dense Deployments of Beyond Wi-Fi 8 Networks](https://mlsanity.com/paper/2608.04050/) (2026)

## Abstract (arXiv)

Multi-access point coordination (MAPC) is a key technology for enhancing throughput in next-generation Wi-Fi within dense overlapping basic service sets. However, existing MAPC protocols rely on static, protocol-defined rules, which limits their ability to adapt to dynamic network conditions such as varying interference levels and topologies. To address this limitation, we propose a novel Agentic AI Wi-Fi framework where each access point, modeled as an autonomous large language model agent, collaboratively reasons about the network state and negotiates adaptive coordination strategies in real time. This dynamic collaboration is achieved through a cognitive workflow that enables the agents to engage in natural language dialogue, leveraging integrated memory, reflection, and tool use to ground their decisions in past experience and environmental feedback. Comprehensive simulation results demonstrate that our agentic framework successfully learns to adapt to diverse and dynamic network environments, significantly outperforming the state-of-the-art spatial reuse baseline and validating its potential as a robust and intelligent solution for future wireless networks.