#None #Huawei #AI Agents #Core Network

The Future of Connectivity: AI-Native Core Networks

In the evolving world of mobile communications, traditional networks have primarily facilitated voice calls, SMS, and mobile internet access. However, the advent of agent-based services signifies a paradigm shift in how these networks operate, necessitating advanced capabilities to manage vast numbers of AI agents effectively. According to Huawei, these next-generation services will demand a core network that comprehends intents, makes intelligent decisions, and seamlessly executes AI-driven tasks.

Why AI-Native Networks are Essential

Huawei posits that implementing an AI-native core network will be critical for this transformation. By embedding artificial intelligence across interfaces, functionalities, and workflows, network operators can evolve beyond mere connectivity, venturing into intelligent network functions tailored for the next wave of digital services. As outlined in Huawei’s report "Intelligent World 2035," the number of AI agents globally could reach an astounding 900 billion by 2035—representing about 100 times the world's population. This burgeoning figure underscores the urgent requirement for core network architectures capable of supporting long-term growth in new connections and services.

As AI devices and applications proliferate, agent-based services are poised to become common scenarios in mobile networks. This marks a shift from merely transporting bits of data to enhancing task-oriented tokens. To address this, Huawei has identified three typical service scenarios crucial for ensuring a robust agent-based user experience:

1. Agent Over New Radio (AoNR)

AoNR is designed to ensure optimal task latency, acknowledging that wearable AI devices often grapple with limitations related to computational power, battery life, and cost. By focusing on maintaining a superior user experience while adhering to stringent end-to-end latency thresholds, AoNR sets the stage for responsive and effective communication between devices and networks.

2. Wide-Area Computing Network (WCN)

The WCN connects computational resources across mobile networks, enabling task-oriented computing scheduling and standardized computing services. This approach amplifies computing efficiency by leveraging the power of the network to facilitate on-demand resource allocation for agent-driven tasks.

3. Agent Computing Network (ACN)

In many complex scenarios, collaboration among multiple AI agents—spread across different domains, enterprises, and ecosystems—is necessary rather than relying solely on individual agents. The ACN promotes secure, dynamic teamwork between specialized agents by incorporating key functionalities such as inter-domain trusted digital identity, competency-based agent recognition, and task-oriented dynamic networking.

Key Characteristics of Next-Gen Core Network Architecture

To effectively bridge the gap between devices and networks, the next-generation core network architecture should integrate three fundamental attributes:

• - Interfaces (From Signaling to Intent): Intent-based interfaces will empower devices to transmit their personalized task requirements—including network, computing, and experiential demands—directly to the network, fostering a more intuitive interaction.

• - Functions (C/U Layers to C/U+DAP Layers): Introducing a dedicated data and AI processing layer (DAP) alongside traditional control and user layers forms an intelligence layer that interprets task intents and dynamically allocates resources in real-time.

• - Processes (From AI Overlay to AI-Native): Deep integration of AI-driven decision-making into fundamental network processes is necessary to synchronize connectivity and computational capacities seamlessly.

Future Phases of AI-Driven Core Network Development

Looking ahead, Huawei envisions two distinct phases in the AI-driven evolution of core networks. The first phase focuses on enhancing customer experience through the incorporation of AI capabilities into existing systems. The second phase will culminate in the establishment of an AI-native core network capable of what Huawei describes as "extended connectivity". This will ensure task-oriented AI services facilitate the efficient execution of digital tasks, pushing the boundaries of connectivity to include complex functionalities like resource provisioning and inter-agent collaboration.

To adapt to these emerging services, a redesign of the network architecture is essential, particularly concerning interaction dynamics, data architecture, and computing frameworks. Moreover, transitioning to AI-native networks necessitates comprehensive cooperation across the ICT ecosystem, encompassing devices, chips, and network structures. This synergy between devices and networks, bolstered by advanced core network architecture, will pave the way for groundbreaking new connections and services—ultimately unlocking numerous business opportunities in the intelligence era.