Under the premise of non-destructive network performance and user experience, we can achieve smart energy saving, reduce the daily power consumption of 5G base stations by more than 30%, and promote the low-cost, efficient operation and sustainable development of 5G networks.

Traditional energy saving is a unified strategy and parameter configuration, which cannot match the real needs of each site on the network, and the solidification of the strategy can easily lead to deterioration of the KPIs of some sites; once the existing network changes, the existing energy saving strategy cannot be used and needs to be re-analyzed and formulated. This energy-saving deployment adopts an AI service navigation strategy. According to changes in traffic demand, the energy-saving solution is analyzed from the scene and busy hours, and the energy-saving solution is adjusted according to the scene to accurately match the energy consumption requirements. Energy-saving functions such as carrier shutdown, achieve a balance between optimal energy conservation and optimal network experience.

On the base station side, a new energy-saving method based on the number of users and the utilization rate of uplink and downlink PRBs has been opened, and ZTE has jointly developed a load forecasting platform, which reports the original data based on the base station, and outputs performance data such as load and number of users through the network management, using time series The prediction algorithm completes the traffic load prediction. At the same time, the optimal energy-saving trigger threshold is dynamically corrected based on AI self-learning, making the single-site energy-saving shutdown time window more intelligent and reasonable, so as to achieve the optimal energy efficiency of the entire network, and fully contribute to the creation of a green, environmentally friendly, intelligent and healthy 5G network.

5G Wireless Industrial Router will benefit from energy-saving. If any interest on 5G industrial router, please refer to: