The 6G Alliance of Network AI (6GANA) was a collaborative initiative launched in April 2021 by major industry players, including China Mobile, Huawei, China Telecom, China Unicom, ZTE, and leading universities such as Tsinghua University and Zhejiang University. Its mission was to integrate AI natively into 6G networks, driving standardisation and fostering the development of AI-centric architectures.
Vision and Objectives
6GANA aimed to transform 6G networks into intelligent platforms, moving beyond the cloud-based AI model of 5G. The goal was to create network AI, where AI capabilities would be embedded directly into the network infrastructure. This shift would enable large-scale distributed training, real-time edge inference, and AI-as-a-Service (AIaaS), making pervasive intelligence accessible to industries.
Key objectives of 6GANA included:
- Native AI Integration: Embedding AI directly into network functions, protocols, and architecture to enable real-time learning and adaptation.
- ICDT Fusion: Combining information, communication, data, and technology into a unified, intelligent ecosystem.
- Redefining the Device-Pipe-Cloud Model: Shifting from centralised cloud AI to distributed network AI, enhancing performance, privacy, and efficiency.
Network AI: Evolving to Handle Multimodal AI
As AI services evolve into multimodal AI—integrating and processing various types of data such as images, voice, and text—the complexity of models is increasing exponentially. These advanced models require massive computing resources and memory, making it difficult to provide them using only on-device AI, which has limited processing power.
To address this, 6G networks are expected to adopt a hybrid approach, where devices and networks collaborate to handle power-intensive AI tasks, such as image generation and 3D rendering. Offloading parts of the AI processing to the network will not only improve efficiency but also reduce the energy consumption of individual devices. This approach will be particularly important for real-time, large-scale AI applications, where network proximity to devices will minimise latency and enhance performance.
In this context, 6GANA introduced a six-level framework to categorise the convergence of networks and AI:
- S0: AI4NET – Applying AI to enhance network performance and automate operations.
- S1: Connection for AI – Providing connectivity for AI services with big data and real-time data transfer.
- S2: S1 + Computing for AI – Adding computing resources within the network to support AI service execution.
- S3: S2 + Data for AI – Offering data services, including data collection and pre-processing, to optimise AI workflows.
- S4: S3 + Algorithm for AI – Incorporating AI model training algorithms into the network infrastructure.
- S5: AI as a Service (AIaaS) – Delivering a fully autonomous orchestrator that manages all of the above resources, offering AIaaS directly from the network.
Impact and Legacy
6GANA’s vision extended beyond traditional telecom infrastructure, aiming to create intelligent, autonomous networks capable of supporting complex, multimodal AI applications across industries. By embedding AI processing capabilities into the network itself, 6GANA anticipated a future where networks would become AI powerhouses, offering AIaaS for a broad range of applications, from industrial automation to real-time immersive experiences.
Although 6GANA is no longer active, its pioneering work laid the foundation for AI-powered 6G networks, influencing industry thinking around AI-native architectures, edge computing, and network intelligence. Its legacy continues to shape the development of intelligent, autonomous communication systems in the 6G era.
Comments
Post a Comment