Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction

This paper presents a new approach for automatic detection of low coverage and high interference 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 and compute harshness metrics, at cluster and cell level, quantifying the extent of the problem. Future work is in motion by adding self-optimization capabilities to the algorithms, which will automatically suggest physical and parameter optimization actions, based on the already developed harshness metrics. The proposed algorithms were validated for a live network urban scenario. 830 3rd Generation (3G) cells were self-diagnosed and performance metrics were computed. The most negative detected behaviors regards high interference control and not coverage verification.