Tracking Down High Interference and Low Coverage in 3G/4G Radio Networks Using Automatic RF Measurement Extraction

This paper presents an automatic approach for the detection of high interference and low coverage scenarios (overshooting and pilot pollution) in Universal Mobile Telecommunications System (UMTS) /Long Term Evolution (LTE) networks. These algorithms, based on periodically extracted Drive Test (DT) measurements (or network trace information), identify the problematic cluster locations for each evaluated cell and compute harshness metrics, at cluster and cell level, quantifying the extent of the problem. The cluster based detection associated with an auto-correlation distance for shadow fading, enables to detect prevailing under performance areas and mitigate detections caused by the radio channel variability. Future work is in motion by adding self-optimization capabilities to the algorithms, which will automatically suggest physical and parameter optimization actions. The proposed algorithms were validated for a live network in both rural and urban scenarios. A total of 173 4\(^{th}\) Generation (4G) cells were self-diagnosed and performance metrics were computed. The most negative sub-performance scenarios concern high interference control in urban environment and low coverage in rural environment.