Multi-Dimensional Resource Management for 6G IoT Networks with Generative Artificial Intelligence
| Reference number | |
| Coordinator | Kungliga Tekniska Högskolan - Avdelningen för teknisk informationsvetenskap |
| Funding from Vinnova | SEK 628 832 |
| Project duration | May 2026 - August 2027 |
| Status | Ongoing |
| Venture | 6G - Competence supply |
Purpose and goal
Present 6G IoT poses severe challenges, especially in dynamically managing its vast multi-dimension resources amid heightened demands for latency, rates, reliability etc. Traditional approaches, particularly those relying on Deep Reinforcement Learning (DRL), have obvious limitations in various and complex 6G IoT networks. In this context, we will explore Generative Artificial Intelligence (GAI) to solve these challenges.
Expected effects and result
The project will lead to technologies improving IoT resource in 6G networks.
Planned approach and implementation
First, we will establish a hypergraph-based framework for multidimensional resource representation and modeling, focusing on service capacity optimization. Next, we will use the Generative Diffusion Model (GDM) to streamline communication intent extraction, facilitate rapid decision-making, and improve network adaptability. Finally, we will leverage GDM to create resilient incentive structures, aiming to ensure fair resource allocation and improve user experience in the 6G IoT environment.