This MDA capability is for the energy saving analysis.
Operators are aiming at decreasing power consumption in 5G networks to lower their operational expense with energy saving management solutions. Energy saving is achieved by activating the energy saving mode of the NR capacity booster cell or 5GC NFs (e.g. UPF etc.). The energy saving decision making is typically based on the load information of the related cells/UPFs, the energy saving policies set by operators and the energy saving recommendations provided by MDAS producer. To achieve an optimized balance between the energy consumption and the network performance, MDA can be used to assist the MDAS consumer to make energy saving decisions.
To make the energy saving decision, it is necessary for MDAS consumer to determine where the energy efficiency issues (e.g. high energy consumption, low energy efficiency) exist, and the cause of the energy efficiency issues. Therefore, it is desirable for MDA to correlate and analyze the energy saving related performance measurements (e.g. PDCP data volume of cells, power consumption, etc.) and the network analysis data (e.g. observed service experience related network data analytics) to provide the analytics results which indicate current network energy efficiency. In some low-traffic scenarios, MDA MnS consumers may expect to reduce energy consumption to save energy. In this case, the MDA MnS consumer may request the MDAS producer to report only high energy consumption issue related analytics results. When the consumer expects to improve energy efficiency, although it may lead to high energy consumption in network or in certain parts of network, then the related issue is the low energy efficiency one. In that case, the consumer may request analytics results related to low energy efficiency issue. So, the target could be to enhance the performance of NF for a given energy consumption. This will result in higher Energy Efficiency of network.
To make the energy saving decision, it is necessary for MDAS consumer to determine which Energy Efficiency (EE) KPI related factor(s) (e.g. traffic load, end-to-end latency, active UE numbers, etc.) are affected or potentially affected. The MDAS producer can utilize historical data to predict the EE KPI related factors (e.g. load variation of cells at some future time, etc.). The prediction result of these information can then be used by operators to make energy-saving decision to guarantee the service experience.
The MDAS producer may also provide energy saving related recommendation with the energy saving state to the MDAS consumer. Under the energy saving state, the required network performance and network experience should be guaranteed. Therefore, it is important to formulate appropriate energy saving policies (start time, dynamic threshold setting, base station parameter configuration, etc.). The MDAS consumer may take the recommendations with the energy saving state into account for making analysis or making energy saving decisions. After the recommendations have been executed, the MDA producer may start evaluating and further analyzing network management data to optimize the recommendations.