What has AI technology brought to the intelligence of wireless networks?

2024-02-28

Intelligent wireless network has become a new trend in the development of the Internet industry. Utilizing technologies such as AI and 5G to achieve efficient, fast, and stable interconnection and interoperability of wireless networks is bringing new energy to the development of industries such as home entertainment and e-commerce.

Recently, ZTE released the "Wireless Network Intelligence White Paper", which integrates AI with various stages of the development of wireless network lifecycle, helping customers cope with various challenges faced in the new era of 5G. The white paper points out that the evolution of network intelligence is a long-term process that needs to be gradually promoted in combination with the current situation of customer networks, the maturity of 5G technology, and network evolution strategies.

The application of wireless network intelligence solutions can bring significant benefits to customers in response to some key scenarios they are currently concerned about. For example, in an automatic deployment solution, the traditional 20 minute single site deployment is reduced to only 3 minutes for 100 sites, and automatic monitoring is implemented to ensure that data is not missed, resulting in an efficiency improvement of hundreds of times; In practical applications, the average energy-saving time of AI energy-saving solutions is 2.5 times that of traditional energy-saving solutions.

After the introduction of artificial intelligence, data+learning will generate a decision that enables the network to meet user needs and achieve high network efficiency standards. Intelligence can be considered in three layers in wireless networks, namely the access layer, terminal layer or edge layer, and cloud layer. From the perspective of operators, the core of network intelligence lies in network parameters (QoS parameters, bandwidth, power, modulation method, transmission rate, etc.) and morphology (routing, slicing, access method, etc.). And these can be automatically adjusted according to parameters such as network resource usage status, business type, user level, and location, in order to better adapt to business needs.

Among them, at the network and business control layer, AI can prioritize the integration of AI's reasoning ability to achieve intelligent network optimization, operation, control, and security for the network and business. Implement KPI optimization, routing optimization, network strategy optimization, etc. at all levels of the network, such as wireless capacity optimization, coverage optimization, load optimization, etc.

The advancement of technologies such as 5G has also had a certain impact on wireless network applications. 5G has three scenarios: firstly, it enhances mobile broadband; The second is low latency and high reliability; The third is the massive Internet of Things. The emergence of these three scenarios should be attributed to the increasing prevalence of wireless network development in multiple corners and scenarios, that is, ubiquity; As demand continues to increase, it becomes more and more scenario oriented.

At the same time, for the low latency and high reliability requirements faced by 5G, the closer you are to users, the better you can make decisions, which introduces mobile edge computing. Mobile edge computing is to introduce better intelligence on the base station side, collect user information and wireless information in time to do intelligent edge processing, which can effectively reduce the cost of intelligent processing. Mobile edge intelligence cannot meet all business needs, and some businesses still need to introduce intelligence in the cloud.

In terms of the home industry, wireless network applications have penetrated into the lives of ordinary people in recent years. Although it will not replace traditional wired networks, it has become an important technology for flexible expansion of traditional wired networks. Generally speaking, the application scope of wireless networks is divided into indoor and outdoor. Indoor applications include all spaces in daily home life, while outdoor applications include villa courtyards, etc. With the continuous maturity of technology, wireless networks are expected to be more deeply applied in the remote control of home electronic products and the interconnection of home devices.

At present, the application of AI technology in network intelligence is still in its early stages, and there is still significant room for improvement in the future. The complex wireless network environment tests AI at multiple levels, including software development, algorithm optimization, and infrastructure construction. During this period, it cannot be separated from the participation of pipeline and equipment vendors, and the assistance of software vendors. Next, industry insiders need to explore and try more in the development of key technologies and the establishment of professional platforms.

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