From RAN Control to Agentic Intelligence: Architecture and Vision for Energy Efficient AI-RAN

• URL: http://arxiv.org/abs/2606.21955v1
• Date: Sat, 20 Jun 2026 09:04:57 GMT
• Title: From RAN Control to Agentic Intelligence: Architecture and Vision for Energy Efficient AI-RAN
• Abstract summary: 6G networks will rely on highly distributed, AI-native Radio Access Networks (RANs)<n>This article proposes an agentic AI-native RAN architecture that bridges O-RAN's structured control with AI-RAN's unified vision.<n>We show how such coordination can improve resource efficiency and reduce operational energy consumption.
• Score: 3.5434399133151744
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Future 6G networks will rely on highly distributed, AI-native Radio Access Networks (RANs), where communication and AI workloads share a common infrastructure. This evolution, combined with increasing deployment density and continuous AI processing, is expected to significantly increase RAN energy consumption. While Open RAN (O-RAN) introduces a programmable and modular control framework through the RAN Intelligent Controller (RIC) and Service Management and Orchestration (SMO), current approaches remain largely policy-driven, limiting adaptive energy-aware coordination across multiple applications. In parallel, AI-RAN promotes the convergence of AI and RAN infrastructures through AI-for-RAN, AI-on-RAN, and AI-and-RAN paradigms, yet efficient mechanisms to jointly orchestrate performance, latency, and energy remain an open challenge. This article proposes an agentic AI-native RAN architecture that bridges O-RAN's structured control with AI-RAN's unified vision. Leveraging semantic intent abstraction and Large Language Model (LLM)-driven coordination, the framework enables adaptive orchestration, conflict resolution, and energy-aware multi-objective optimization across heterogeneous workloads. Through representative AI-for-RAN and AI-on-RAN use cases, we show how such coordination can improve resource efficiency and reduce operational energy consumption, paving the way toward sustainable 6G networks.

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