SoftBank has implemented an innovative method for radio access network design from Ericsson, based on machine intelligence.
The service groups cells in clusters and takes statistics from cell overlapping and potential to use carrier aggregation between cells into account, thus reducing operational expenditure and improving network performance. Compared to traditional network design methods, it cut the lead time by 40 percent.
The foundation for the method is a thorough analysis of the actual radio network environment, for example taking cell coverage overlap, signal strength and receive diversity into consideration. The high number of possible relations between cells as well as considerations for network evolution, calls for substantial computational power and state-of-the-art machine learning techniques.
This complex task was a challenge that Ericsson solved by implementing a design concept based on network graph machine learning algorithm. SoftBank was able to automate the process for radio access network design with Ericsson’s service. Big data analytics was applied to a cluster of 2000 radio cells and data was analyzed for the optimal configuration.
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