Toward Autonomous O-RAN: A Multi-Scale Agentic AI Framework for Real-Time Network Control and Management
arXiv:2602.14117v2 Announce Type: replace-cross Abstract: Open Radio Access Networks (O-RAN) promise flexible 6G network access through disaggregated, software-driven components and open interfaces, but this programmability also increases operational complexity. Multiple control loops coexist across the service management layer and RAN Intelligent Controller (RIC), while independently developed control applications can interact in unintended ways. In parallel, recent advances in generative Artificial Intelligence (AI) are enabling a shift from isolated AI models toward agentic AI systems that
The increasing complexity of 6G Open Radio Access Networks (O-RAN) necessitates advanced automation, and recent strides in generative AI are enabling the development of sophisticated agentic systems to manage this complexity.
This development signifies a crucial step towards fully autonomous network operations, reducing human intervention and potentially enhancing network efficiency, security, and scalability for future telecommunications infrastructure.
Network management in O-RAN environments will shift from human-centric oversight and pre-programmed automation to intelligent, self-adapting AI agents capable of real-time control and optimization across multiple layers.
- · Telecommunications providers
- · AI software developers
- · Network equipment vendors
- · 6G infrastructure developers
- · Traditional network operators (without AI upskilling)
- · Legacy network management software vendors
O-RAN deployments become significantly more efficient and less prone to human error due to autonomous agentic AI.
The demand for specialized AI talent in telecommunications engineering increases, driving new educational and training programs.
National security concerns arise regarding the resilience and trustworthiness of AI-controlled critical communication infrastructure, prompting new regulatory frameworks for autonomous network systems.
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Read at arXiv cs.AI