A novel localization C# framework for RAN optimization using extreme programming methodologies

With the current traffic increase in cellular networks, it becomes demanding and complex for operators to manage and optimize its networks in order to provide enhanced Quality of Service (QoS) to users. One of the network optimization option is to use drive-tests data. Unfortunately, drive-tests are cost demanding, and are limited to the outdoor environments where radio measurements have been performed. A more cost effective solution is proposed in this paper as an alternative to drive-tests. A framework that gathers and locates exchanged signalling (called traces) between the real network users and network elements is proposed, enabling indoor/outdoor network optimization. To achieve that, a C# application was developed, using Extreme Programming methodologies, which were applied to produce an high quality and robust application. After event localization, a comparison was performed with drive tests data, presenting a 0.3 dB and 2.4 dB average and median error, respectively.