With the cloud and NFV transformation of telecom networks, integration of 5G and IoT, and development of diverse industrial applications, the operations of telecom networks will face unprecedented challenges in the 5G era. These challenges involve complex networking, diverse services and personalized experience.
Therefore, the challenges of network operations that come with the 5G era will be significant. The advanced automated operations are gradually forming a gap with the traditional operations based on expert experience. Automated and intelligent network operations will be the just need in the 5G era. Artificial intelligence (AI) technology has intrinsic advantages in solving high-volume data analysis, cross-domain feature mining, and dynamic strategy generation, and will create new modes and capabilities for 5G network operations.
In the future, based on the cloud infrastructure, the network that combines 5G, AI and IoT will gradually become the intelligent center of digital society and promote intelligent interconnection of all things.
As the world's leading telecom solution provider and 5G leader, ZTE has actively combined the AI technology with 5G to carry out automation and intelligence in related fields covering 5G wireless, cloud, slicing, bearer and operations services. Moreover, ZTE has also actively participated in the development of relevant standards and contributions to open source technologies.
A 5G network serves as the fundamental infrastructure that can support digital development of various industries and provide differentiated services for all industry scenarios. To support a variety of industry applications and business scenarios in a flexible and on-demand manner, the 5G network will be built with cloud service-based architecture (SBA) to meet the future long-term development needs. 5G RAN implements CU/DU separation. The CU can support cloud or dedicated hardware deployment, flexibly adapting to various scenarios. The service-based architecture allows for a converged core of 2G, 3G, 4G and 5G networks, meeting the needs of smooth evolution, collaborative development and long-term coexistence.
5G cloud and service-based architecture is the foundation to support various industry applications and business scenarios. Enabling efficient, flexible, low-cost, easy operations with openness and innovation will be the core competitiveness of operators in the 5G era. This is also a key trend of 5G network intelligence and its main requirements involve:
Faced with the challenges of 5G development and the needs to introduce intelligence, the combination of AI and telecom networks will be ubiquitous in 5G networks. An intelligent 5G network can be achieved by introducing algorithm models and intelligent engines into different levels of the network, as shown in Fig. 1.
Based on the cloud and service-based architecture, 5G network has distinct differences at different network levels. The upper layer is more centralized and has higher requirements for cross-domain analysis and scheduling capabilities such as E2E slice orchestration and management and global cloud resource coordination that rely on the centralized smart engine (SE) for centralized global strategy training and reasoning. The lower layer closer to the end side focuses on intelligence enhancement of professional subnets or single network elements. Access network, bearer network, and core network introduce Lite SE (LSE) to enhance intelligence of subnets or the sub-slice domain such as management strategies and smart operations. Edge devices such as MEC and 5G gNB introduce real-time SE (RSE) to achieve real-time or quasi-real-time intelligence at the edge.
The AI algorithm model and smart engines at various levels can be deployed based on the hardware computing environments in 5G networks. The combination of engines, model components, and application algorithms with different network functional entities enables 5G network intelligence.
The basic hardware environments where AI capabilities are deployed in a 5G network can be centralized GPU clusters, general-purpose servers or blade servers, or 5G base stations. The intelligent capability layer (AI layer) contains the engine layer, model layer and application layer (Fig. 2).
The combination of various AI capabilities can be integrated into ZTE 5G products including 5G NR, 5G cloud core, 5G UME, VMAX and BigDNA to meet specific needs of network deployment. ZTE's AI-assisted intelligent networks will help operators plan their networks more scientifically with more accurate fault location capabilities, lower operation costs, and business capabilities that better meet user needs, so that they can survive the fierce competition in the coming 5G era.
[Keywords] Artificial intelligence (AI), 5G network operations