Radio Channel Degradation Detection and Diagnosis Based on Statistical Analysis

In complex radio environments like cellular mobile networks, the quality of the radio channel strongly affects the service quality experienced by users. Degraded channel quality makes users unsatisfied and thus results in revenue loss for the operator. This is particularly important as most of the cell level faults result in channel degradations. As the complexity of commercial cellular networks is increasing, the need for reliable automated detection of cells with degraded radio quality has become essential. Channel degradation detection alone is already a challenging task but finding the root cause is usually even harder. Human experts with decades of experience in the telecommunication domain are having hard times during investigating the root cause of degraded service quality. Our demonstration introduces a framework that is on one hand capable to detect cells with channel degradations and on the other hand differentiate between possible root causes. The showcases are implemented in a simulated 3GPP Long Term Evolution (LTE) environment animated on a 3D graphical scene.