SoftBank is using machine-learning software developed by Ericsson for advanced radio network design in the Tokai region. 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. The machine learning evaluates cell coverage overlap, signal strength and receive diversity. Big data analytics was applied to a cluster of 2000 radio cells and data was analyzed for the optimal configuration.
Ericsson’s centralized and elastic radio access network design is sold as a service and supports LTE networks. Ericsson says that compared to traditional network design methods, the ML approach cuts the lead time by 40 percent.
Ryo Manda, Radio Technology Section Manager at the Tokai Network Technology Department of SoftBank, says: “We applied Ericsson’s service on dense urban clusters with multi-band complexity in the Tokai region. The positive outcome exceeded our expectations and we are currently proceeding in other geographical areas with the same method and close cooperation with Ericsson.”
Peter Laurin, Head of Managed Services at Ericsson, says: “There is a huge potential for machine learning in the telecom industry and we have made significant investments in this technology. It is very exciting to see that the new methods have been successfully applied in SoftBank’s network. There is a strong demand for this type of solutions and deployments of this service to other tier-one operators in other regions are ongoing.”
