# 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  
#### 3.2.1 Key Performance Indicators for 5G Traffic Types  
The 5G-connected devices are bound to have varying levels of capabilities importance, such as data rate, connection density, or latency (Figure 7). The key minimum technical performance requirements with corresponding metrics definitions for the 5G radio interface are defined in [13]. In addition to these metrics, the report in [14] maps the three 5G usage scenarios (_eMBB_, _mMTC_, and _URLLC_) into evaluation criteria. With these documents, the radio interface evaluation procedure is designed in such a way that the overall performance of the radio interface can be fairly and equally assessed on a technical basis, ensuring that the overall 5G objectives are met. There are many drivers behind the anticipated importance of the 5G characteristics, depending on the detailed circumstances. The enhanced mobile broadband usage scenario comes with new application areas and requirements for improved performance and an increasingly seamless user experience. This usage scenario includes wide-area coverage and hotspot, which have different requirements. For the hotspot case, i.e., for an area with high user density, very high traffic capacity is needed, whereas the requirement for  
Figure 6: Applying AI/ML-based 5G RAN performance evaluation based on a 3 GPP-assumed paradigm. Figure 7: The importance of key capabilities in different 5G usage scenarios [3]. mobility is low and the user data rate is higher than that of wide area coverage. For the wide area coverage case, seamless coverage but medium to high mobility are desired, with a much-improved user data rate. However, the data rate requirement may be relaxed compared to a hotspot. Overall, the variety of smart devices (e.g., smartphones, tablets, televisions, etc.) and a wide range of applications requiring a large amount of data traffic, accelerate demand for wireless data traffic. Since the _eMBB_ is expected to accommodate the increasing traffic demand and to provide gigabit-per-second user data rate services, a data rate becomes a pillar measure for the capability assessment [3]. The support for ultralow latency and high-reliability connections corresponds to human- and machine-centric communication. A human's expectation of instantaneous connectivity wherein applications need to exhibit \"flash\" behaviour without waiting times pertains to communication which becomes an enabler for the development of applications, e.g., in health, safety, office, entertainment, and other sectors. For applications based on machine-centric communication with real-time constraints (e.g., driverless cars, enhanced mobile cloud services, real-time traffic control optimization, emergency, and disaster response, emergency rescue services, control of industrial manufacturing or production processes, remote medical surgery, e-health, etc. ), reliability understood as the capability of transmitting a given amount of traffic within a predetermined time duration with high success probability is a key demand [10]. The massive machine type communication corresponds to the presence of a large number of concurrent users, for example in a crowd with a high traffic density per unit area and a large number of handsets and machines/devices per unit area. Hence, primarily the use case envisions a certain number of devices per unit area fulfilling a specific quality of service [10], which should be measurable by the network as a certain level of connection density. These fundamental 5G characteristics can be measured according to simulation, analytical, or inspection-based 5G performance evaluation methods [12]. To select the 5G traffic-specific indicators for ML-driven data collection, the key performance indicators defined specifically for analytical evaluation methodology [12] apply (Table 1).