From Connectivity to Autonomy: The Dawn of Self-Evolving Communication Systems
It addresses the problem of enabling autonomous communication systems for industrial IoT and digital manufacturing applications, though it appears incremental as it builds on existing 6G network management techniques.
This paper envisions 6G as a self-evolving telecom ecosystem using AI-driven intelligence to enable dynamic adaptation beyond static connectivity, emphasizing improved real-time decision-making, efficiency optimization, and latency reduction in networked control systems.
This paper envisions 6G as a self-evolving telecom ecosystem, where AI-driven intelligence enables dynamic adaptation beyond static connectivity. We explore the key enablers of autonomous communication systems, spanning reconfigurable infrastructure, adaptive middleware, and intelligent network functions, alongside multi-agent collaboration for distributed decision-making. We explore how these methodologies align with emerging industrial IoT frameworks, ensuring seamless integration within digital manufacturing processes. Our findings emphasize the potential for improved real-time decision-making, optimizing efficiency, and reducing latency in networked control systems. The discussion addresses ethical challenges, research directions, and standardization efforts, concluding with a technology stack roadmap to guide future developments. By leveraging state-of-the-art 6G network management techniques, this research contributes to the next generation of intelligent automation solutions, bridging the gap between theoretical advancements and real-world industrial applications.