# LLM-Driven Adaptive 6G-Ready Wireless Body Area Networks: Survey and Framework

arXiv: https://arxiv.org/abs/2508.08535 · HTML: https://mlsanity.com/paper/2508.08535/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 39 references that are in the map.
- First posted on arXiv 12 Aug 2025.

## Builds on (most cited first, 10 of 10)

- [Self-Refine: Iterative Refinement with Self-Feedback](https://mlsanity.com/paper/2303.17651/) (2023)
- [A Survey on Multimodal Large Language Models](https://mlsanity.com/paper/2306.13549/) (2023)
- [PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://mlsanity.com/paper/2502.11221/) (2025)
- [LINKs: Large Language Model Integrated Management for 6G Empowered Digital Twin NetworKs](https://mlsanity.com/paper/2412.19811/) (2024)
- [ASSERTIFY: Utilizing Large Language Models to Generate Assertions for Production Code](https://mlsanity.com/paper/2411.16927/) (2024)
- [Streamlining Security Vulnerability Triage with Large Language Models](https://mlsanity.com/paper/2501.18908/) (2025)
- [Secure coding for web applications: Frameworks, challenges, and the role of LLMs](https://mlsanity.com/paper/2507.22223/) (2025)
- [Advanced U-Net Architectures with CNN Backbones for Automated Lung Cancer Detection and Segmentation in Chest CT Images](https://mlsanity.com/paper/2507.09898/) (2025)
- [In-The-Wild Interference Characterization and Modelling for Electro-Quasistatic-HBC with Miniaturized Wearables](https://mlsanity.com/paper/2011.00300/) (2020)
- [Secure and Scalable Blockchain Voting: A Comparative Framework and the Role of Large Language Models](https://mlsanity.com/paper/2508.05865/) (2025)

## Abstract (arXiv)

Wireless Body Area Networks (WBANs) enable continuous monitoring of physiological signals for applications ranging from chronic disease management to emergency response. Recent advances in 6G communications, post-quantum cryptography, and energy harvesting have the potential to enhance WBAN performance. However, integrating these technologies into a unified, adaptive system remains a challenge. This paper surveys some of the most well-known Wireless Body Area Network (WBAN) architectures, routing strategies, and security mechanisms, identifying key gaps in adaptability, energy efficiency, and quantum-resistant security. We propose a novel Large Language Model-driven adaptive WBAN framework in which a Large Language Model acts as a cognitive control plane, coordinating routing, physical layer selection, micro-energy harvesting, and post-quantum security in real time. Our review highlights the limitations of current heuristic-based designs and outlines a research agenda for resource-constrained, 6G-ready medical systems. This approach aims to enable ultra-reliable, secure, and self-optimizing WBANs for next-generation mobile health applications.