| Summary: | This paper presents a novel Quality of Experience model (QoE), for 3G voice calls; it estimates a user perceived quality, in a Mean Opinion Score (MOS) scale, by evaluating several Radio Frequency (RF) channel metrics. Real Drive Test (DT) data with MOS measurements have been used as reference data, in order to produce a new MOS prediction model, using machine learning techniques. The new developed model enables the application of QoE as a possible network optimization criteria. Furthermore, it is showcased a generic framework to optimize antenna physical parameters. Using this framework, an algorithm was implemented which empowers the network MOS estimation by using the developed QoE model. A Root Mean Square Error (RMSE) of 9% was achieved, on the MOS prediction, using the developed model. Concerning the MOS antenna physical parameters optimization, it resulted in an average network performance gain of 5% comparatively to a interference control generic approach.
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