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Applications of machine learning to the planning of 5G-era small cell networks

Ever-growing demand for mobile data is driving network densification with the deployment of small cells. However, the identification of sites which can effectively capture traffic not served by the existing network is a complex optimisation problem that increasingly requires a computational approach. Here we consider the level of precision required in small cell planning and share two case studies of where machine learning techniques have been applied.

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