A Performance Scoring Approach for QoS Optimization in Private 5G Networks

Performance benchmarking is crucial for optimizing networks, including 5G Non-Public Networks (5G-NPN). Since one of the major advantages of 5G-NPN is to guarantee Quality of Service (QoS), ensuring optimal performance for their diverse applications is critical. This requires adjustments and testing of various radio-related parameters. Also, performance analysis and benchmarking need to be done based on the evaluation of relevant Key Parameter Indicators (KPIs) in order to identify the parameter set for the optimum performance for each application’s requirements. Many published results on performance benchmarking often lack transparency in their scoring methods. Additionally, QoS benchmarking evaluation for 5G-NPN use cases needs further steps due to the varying ranges of their KPIs. For example Block Error Rate (BLER) is mostly represented by percentage, while Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ) are negative values.3GPP in TR 103.559 outlines practices for benchmarking network QoS, with a focus on Speech and multimedia Transmission Quality (STQ). This paper extends these outlines to evaluate 5G-NPN performance by defining a multi-objective function. We select a specific 5G-NPN use case as an example and apply four tests with varying network configurations. After each test, we collect most relevant 5G KPIs. To facilitate comparison, all KPIs are rescaled to a common scale. Additionally, we assign weights to each KPI based on its significance in the chosen use case. By combining rescaling and weight assignments, we propose a single metric that effectively characterizes the overall network performance for 5G-NPNs based on their specific use case requirements.