The rapid development of artificial intelligence (AI) is bringing revolutionary changes to various industries and ushering in a new era of innovation. Groundbreaking artificial intelligence models such as OpenAI's ChatGPT and Sora, and Google's Gemini are at the forefront of this change, providing users with a broader realm of creativity and imagination, opening up unprecedented possibilities. Artificial intelligence models are fundamentally reshaping the fabric of society and daily life by improving the ability to generate new ideas, solve complex problems, and automate routine tasks.

The integration of 5G and artificial intelligence is an inevitable trend, bringing more possibilities for new business models and applications. As the edge node closest to the user, AI processing on the 5G network can effectively reduce data transmission delays, improve data processing efficiency, and reduce AI application costs. The 5G network provides large bandwidth, high speed, and low latency, which is very suitable for supporting the connection and computing needs of distributed AI computing. The integration of 5G and AI can not only achieve flexible collaboration between cloud and network, but also provide stronger intelligent capabilities, allowing 5G to adaptively optimize and adjust according to data characteristics and scene requirements, improving network performance and efficiency.

The integration of 5G and AI, the growth of new 5G-A capabilities, and the exploration of new scenarios require a lot of computing power. Therefore, integration of communication and computing infrastructure is required. On top of 5G-ABBU, the integration of 5G and AI at edge nodes brings about a revolution in traditional network resource management, enabling user-centered experience and precise resource allocation based on network service capabilities, business needs and UE capabilities. The ultimate user experience. Higher energy efficiency and operational efficiency. Adjust resource allocation and scheduling strategies in real time through precise analysis of traffic and data packets.

Taking Wuhan Iron and Steel as an example, remote control of cranes is a typical application. Uplink needs to transmit large-bandwidth video, and downlink needs to transmit high-reliability control instructions. Based on AI learning and recognition of video data and control instructions, differentiated scheduling strategies are implemented. For example, video data identifies I frames (key frames of pictures) and uses smooth scheduling to avoid "I frame" conflicts; control instructions use ML to predict the sending of data packets and perform accurate scheduling, which not only ensures the reliability of the control instructions, but also It also reduces the usage of system resources. 5G-ABBU also supports the deployment of third-party applications, such as 5G-based V2X applications.

In summary, the integration of 5G and artificial intelligence has brought significant opportunities and challenges to the development and monetization of 5G networks. It enables innovative applications and business scenarios to fully unleash the value of 5G networks, such as deterministic connection guarantees, edge rendering, V2X applications, etc. These new applications and services can significantly increase the revenue of operators and service providers, serving B2C, B2B and new economic development.

2024 is the first year of 5G-Advanced (5G-A) commercialization. Driven by new technologies, new services, and new scenarios, the boundaries of communication networks are constantly expanding. 5G-A is not only the key to the development of 5G in the next 10 years, but also the key to shaping the future digital society.