From Connectivity to Autonomy: The Dawn of Self-Evolving Communication Systems
Nezami, Zeinab, Shah, Syed Danial Ali, Hafeez, Maryam, Djemame, Karim, Zaidi, Syed Ali Raza
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
May-30-2025
- Country:
- Europe (0.28)
- North America > United States
- California (0.14)
- Genre:
- Research Report > New Finding (0.34)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Government (1.00)
- Law (0.69)
- Telecommunications (0.69)
- Technology:
- Information Technology
- Communications > Networks (1.00)
- Architecture > Real Time Systems (1.00)
- Artificial Intelligence
- Representation & Reasoning > Agents (1.00)
- Natural Language (1.00)
- Machine Learning > Neural Networks
- Deep Learning (0.94)
- Information Technology