AgentxGCore: Agentic AI for Next-Generation Mobile Core Network

Researchers propose an AI-native architecture for Next Generation Mobile Networks (NextG), leveraging Large Language Models (LLMs) and Agentic AI to enhance network management and operation.

The Next Generation Mobile Networks (NextG) will adopt an AI-native architecture on the Core Network (CN), according to a research paper submitted on 29 May 2026^[1]. The Third Generation Partnership Project (3GPP) has extended the cellular CN with new functions, but these are limited by a centralized approach. The proposed architecture, called AgentxGCore, integrates Agentic AI and LLMs to enable continuous interaction with the network. AgentxGCore is an Agentic AI-Native layer that extends the 3GPP architecture, enabling a system based on existing APIs across the Beyond Next Generation Core (xGC) domain^[1]. Another research paper, submitted on 14 May 2026, discusses two AI systems: CMBEvolve and CosmoEvolve. CMBEvolve targets tasks with explicit quantitative objectives and improved benchmark scores through code evolution^[2]. CosmoEvolve, on the other hand, targets open-ended scientific workflows and identified non-trivial pair- and scale-dependent behaviour. The proposed AI-native architecture is expected to enable self-organization and self-adaptation in NextG networks.