Ciocarlie, G., Lindqvist, U., Nitz, K., Novaczki, S., & Sanneck, H. (2014, 5-9 May). DCAD: Dynamic Cell Anomaly Detection for operational cellular networks. Paper presented at the IEEE/IFIP Network Operations and Management Symposium (NOMS’14), Krakow, Poland.
Abstract
The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. In this paper, we present Dynamic Cell Anomaly Detection (DCAD), a tool that implements an adaptive ensemble method for modeling cell behavior [5], [6]. DCAD uses Key Performance Indicators (KPIs) from real cellular networks to determine cell-performance status; enables KPI data exploration; visualizes anomalies; reduces the time required for successful detection of anomalies; and accepts user input.