AI-Native Core
Artificial Intelligence-Native 6G Core Architecture
A 6G core architecture designed from the ground up with embedded machine learning models for autonomous control, intent-driven optimization, and predictive resource allocation.
Technical Explanation
Unlike 5G, where AI/ML functions were bolted on as standalone analytics entities (such as NWDAF), the 6G AI-Native Core integrates neural network inference and training primitives directly into the Service-Based Architecture. Every Network Function (NF) possesses native telemetry streaming, localized micro-inference agents, and closed-loop reinforcement learning capabilities. This allows millisecond-level automated healing, proactive network slicing, predictive traffic routing, and intent-driven dynamic topology reconfiguration without human intervention.
Key Functions
- Autonomous closed-loop orchestration across all control and user plane network functions
- Distributed federated learning across multi-vendor edge nodes without raw data egress
- Continuous predictive lifecycle management of network slices and compute workloads
- Natural language intent translation into deterministic policy and routing graphs
- Self-optimizing energy governance dynamically powering down dormant microservices