Digital Twin Enabled Human–AI Collaboration Framework for Autonomous Wireless Network Management
Keywords:
6G Network Management, Digital Twin (DT), Human-AI Collaboration, Explainable AI (XAI), Autonomous Wireless NetworksAbstract
The next generation of wireless networks is moving to 5G-Advanced and 6G, which have a high complexity and dynamic operation demands never seen before. Although Artificial Intelligence (AI) provides an avenue to autonomous network management, black-box models pose a significant danger in terms of safety, interpretability, and regulatory compliance. The current article suggests the implementation of a new framework of Digital Twin Enabled Human-AI Collaboration that may close the gap between completely automated systems and human knowledge. The framework allows for checking AI-driven optimization actions against real-world limits by using a detailed digital twin, which serves as a safe simulation space. The architecture incorporates four domain-specific layers: physical telemetry, digital twin simulation, human-AI collaboration, and explainability. The three different types of human-managed oversight that contribute to policy co-evolution. The framework is a guide for creating safe, easy-to-understand, and constantly learning systems that ensure computer efficiency works well with human understanding, improving how resources are used and reducing costs.
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