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One of the main concerns of telecommunications operators is related to network coverage. A weak coverage can lead to a performance decrease, not only in the user experience, when using the operators' services, such as multimedia streaming, but also in the overall Quality of Service. This paper presents a novel cloud-based framework of a semi-empirical propagation model that estimates the coverage in a precise way. The novelty of this model is that it is automatically calibrated by using drive test measurements, terrain morphology, buildings in the area, configurations of the network itself and key performance indicators, automatically extracted from the operator's network. Requirements and use cases are presented as motivations for this methodology. The results achieve an accuracy of about 5 dB, allowing operators to obtain accurate neighbour lists, optimise network planning and automate certain actions on the network by enabling the Self-Organising Network concept. The cloud implementation enables a fast and easy integration with other network management and monitoring tools, such as the Metric platform, optimising operators' resource usage recurring to elastic resources on-demand when needed. This implementation was integrated into the Metric platform, which is currently available to be used by several operators.

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With the increasing number of mobile subscribers worldwide, there is a need for fast and reliable algorithms for planning/optimization of mobile networks, especially because, in order to maintain a network’s quality of service, an operator might need to deploy more equipment. This paper presents a quick and reliable way to automatically plan a set of frequencies in a cellular network, using both cloud technologies and linear programming. We evaluate our pattern in a realistic scenario of a Global System for Mobile communications protocol (GSM) network and compare the results to another already implemented commercial tool. Results show that even though network quality was similar, our algorithm was twelve times faster and used four times less memory. It was also able to frequency plan seventy cells simultaneously in less than three minutes. This mechanism was successfully integrated in the professional tool Metric, and is currently being used for cellular planning. Its extension for application to 3/4/5G networks is under study.

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