# Modelling of ML-Enablers in 5G Radio Access Network-Conceptual Proposal of Computational Framework
## 3 Applying AI/ML into 5G RAN: Proposed Methodology
### Input Data--Classification Analysis
#### 3.2.2 Key Performance Indicators for RAN Optimization Use Cases  
For RAN performance optimization, three use cases are addressed: coverage optimization, mobility optimization, and _QoS_ optimization. Radio coverage is essential information for network planning, network optimization, and backend network management activities, such as network dimensioning, CAPEX/OPEX planning, and marketing. A detection of coverage problems (e.g., coverage holes, pilot pollution, low user throughput, etc.) in specific areas, e.g., based on customer complaints and along roads or train lines, is also crucial for network operators to be aware of the coverage shortages in the networks they provide. Coverage is easily noticed by a customer through the terminal uplink signal (e.g., strong radio signal or out-of-service area indication). Downlink signal perception is also an important criterion by which many customers judge the performance of the network, as poor coverage will impact the user experience in terms of call setup failure, call drop, or voice quality. Mobility optimization is an important part of network operation, as information about mobility problems or failures can also be used to identify localized lack of coverage or the need to adapt the network parameters setting, e.g., in order to avoid too early or too late handover and to improve the handover success rate and overall network performance. Verification of the quality of service (_QoS_) is another key objective of the network performance analysis, as it allows the detection of critical conditions and determining the need to change the network configuration, parameter settings, or capacity extension. Especially, in order to check if the quality of service experienced by the end user is in line with the performance target defined in the planning strategy and offered to the end user. The _QoS_ verification allows the assessment of the user experience, e.g., in terms of the user throughput. Hence, it has become an important key performance indicator (KPI) in network deployments for operators. Accordingly, the SON and MDT functionalities gather autonomous data collection from customers for network coverage, mobility, and _QoS_ optimization [9]. Technically, the coverage level collected in MDT is expressed by recorded measurement quantities, such as received signal reference power (_RSRP_), received signal reference quality (_RSRQ_), or signal-to-interference and noise ratio (_SINR_), including the measurements' values recorded in the event of radio link failure (RLF). The closer to the failure, the lower the value of the radio signal level is perceived by the user. The same measurement quantities check is fundamental in mobility events management (i.e., handovers), as it indicates a potential drop of the serving signal and hints the network to react. An additional measure for 5G traffic assessment, mobility optimization, is mobility interruption time, which denotes the shortest time duration supported by the system during which a user terminal cannot exchange user plane packets with any base station during transitions. It includes the time required to execute any radio access network procedure, radio resource control signaling protocol, or other message exchanges between the mobile station and the radio access network. The mobility interruption time corresponds to the evaluation of the latency introduced by the system, for verifying whether or not it is small enough in terms of satisfying some predefined use-case-dependent latency requirements. For _QoS_ Optimization, latency and throughput are metrics explicitly characterizing the stringent _QoS_ requirements on the reliability of a target user experience. The outlined measurements for RAN optimization are accessible for collection through MDT procedures, wherein RRC (radio resource control) signaling and RRC data are utilized.